text:
Neither Genes nor Choice: Same-Sex Attraction Is Mostly a Unique Reaction to Environmental Factors. [Journal of Human Sexuality 3: (2011)]
- Martina Barnett
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1 : Same-Sex Attraction Is Mostly a Unique Reaction to Environmental Factors [Journal of Human Sexuality 3: (2011)] by Neil E. Whitehead 8 8 Research Institute of Radiation Biology and Medicine, Hiroshima University, Kasumi 1-2-3, Hiroshima , Japan. Address for Correspondence: N. E. Whitehead, 54 Redvers Drive, Lower Hutt, New Zealand,
2 Abstract This paper uses the seven largest twin registry studies to emphasize that samesex attraction (SSA) is mostly caused neither by genetics (weak to modest influence) nor direct shared environment (very weak), but by many nonshared individualistic events and reactions, none of which is more than a small minority of total influences, and may well be differing reactions to shared environment. Twin studies sum up all influences (known and yet to be found) and their interactions, so this conclusion about the importance of nonshared factors is unlikely to change with future research into biological or social causes. The mean genetic percentages* for men and women are 22 and 33% respectively and are not significantly different statistically. They are almost certainly maxima, likely to halve with further research. Recent findings of nonshared environmental epigenetic causes (genetic expression influenced by the environment) lead again to a conclusion that the genetic influence has possibly been overstated. Nor is deliberate choice of orientation significant; even for adult sexual choice (e.g., heterosexual mate selection), chance predominates. For the development of sexual orientation (ten being the mean age of first attraction), deliberate choice must be a very unusual event. * Erratum A misleading phrase has been removed 82
3 Introduction Over the last fifty years, prolonged debate has raged over the question of where same-sex attraction (SSA) originates is it in prenatal factors, such as genes, or postnatal factors, such as the style of family upbringing? The two groups of protagonists were mainly biologists (who believed in genetic causes) and psychologists (who believed in environmental causes). The purpose of the present paper is to present the evidence that idiosyncratic factors overshadow both the prenatal and parental (environmental) factors. This paper posits that SSA is mostly neither innate nor directly a matter of upbringing or social factors, but rather results from unique reactions to personal experiences. This conclusion is not likely to change with future research. A study of most social factors possibly connected with SSA found that only a small percentage of overall SSA was accounted for by any specific influence, though all influences on adolescents taken together seemed highly significant (Bell, Weinberg, & Hammersmith, 1981). A later study confirmed those findings (Van Wyk & Geist, 1984). Thus, although social/family factors as a whole were quite significant, they were not significant individually. Research showed that there were many paths to SSA, and any given factor affected only a small minority of individuals. Obviously, some individual factors such as sexual abuse were very important to the individuals involved. Bell, Weinberg, and Hammersmith (1981) then totally erroneously stated that SSA was fixed and permanent in a person from childhood on in other words, there was tracking from childhood SSA to adolescent SSA and on to adulthood. Hence, they concluded that their finding of significant social effects as a whole was only a statistical artifact. The most significant single influence they found was childhood gender nonconformity. It used much weaker criteria than full Gender Identity Disorder as understood today, but even as the most significant single influence, it directly led to adult SSA in only 12% of cases a weak effect. The literature has subsequently stated erroneously that the work by Bell, Weinberg, and Hammersmith (1981) disproved that social factors had any general bearing 83
4 on SSA. Rather, Bell et al. could not demonstrate much importance for individual factors. This will be discussed in more depth in a forthcoming paper (in preparation). Reacting to their modest result for individual social influences, Bell, Weinberg, and Hammersmith (1981) without actual evidence thought biological factors might be predominant. They did not discuss a possible role for chance, which from their data alone could have been a predominant part of the variance. The present paper, however, finds using twin studies, that chance (nonshared environmental factors) is indeed predominant, and shows that biological factors like genetic factors are likely to contribute less than 20% of the variance in the development of SSA. The argument in this paper tries to reconcile some other contradictory findings weak social factors for production of SSA being shown in sociological studies, but strong factors being found in individual clinical studies by suggesting that erratic (unique) individualistic reactions to shared social factors are important as causes of SSA. Many nontwin studies of various possible correlative biological factors contributing to SSA followed the 1981 paper (Blanchard, 2008; Kraemer, Noll, Delsignore, Milos, Schnyder, & Hepp, 2006). But none of the subsequent studies found a universal biological factor that might account for most SSA. The large number of such biologically oriented papers (about two dozen a year in PubMed alone) makes it superficially appear that biological factors must sum to a strong influence. However, since there can be overlap, synergistic, or competing influences, a summary measure is highly preferable such as from twin studies. This paper demonstrates that twin study calculations show all biological factors including those yet to be found sum to only a weak to modest effect. In this paper, identical twins will be identified as mz (monozygotic), and fraternal twins will be identified as dz (dizygotic). 84
5 Twin Studies as a Measure of the Various Contributions to SSA Influences A central concept in twin studies is explaining the variation of something in the population such as SSA by calculating the relative contribution of genetics, shared postnatal environment, and nonshared postnatal environment (unique experiences or unique reactions to shared experiences). The early post-world War II SSA studies by Kallmann (Kallmann, 1952a; Kallmann, 1952b) were performed on identical twins who were also mental patients. These studies found an overall 92% concordance for SSA (rather than the 100% sometimes quoted). These findings were never repeated in subsequent samples, possibly partly due to very lax and anecdotal SSA diagnostic criteria. Mz concordance is a simplified form of twin studies and compares shared and nonshared factors only. If the concordance was as high as Kallmann claimed, it would have meant shared factors (genetic and/or family factors) were very strongly influencing SSA development. Subsequent studies have not supported that finding. Later studies followed the classical twin research design of comparing concordance in both mz and dz twins. Concordance in mz twins shows the influence of genetics, and concordance in dz twins allows for shared nongenetic influences. The greater the difference between the concordance of mz and dz twins, the greater the genetic influence. SSA research used samples drawn from the gay/lesbian/bisexual (GLB) community by a volunteer or snowball system, but at the beginning of the new millennium such studies were shown to have been subject to the known general problem that similar mz twins tend to volunteer for studies on a publicized topic and dissimilar mz twins do not (Kendler & Eaves, 1989). The results ultimately proved to be a great deal more biased than researchers had thought possible. The genetic influence fraction in those early studies, about 50%, is now generally believed to be significantly inflated but, unfortunately, it is still quoted. This paper which follows twin studies mainly since the year 2000 will suggest the true answer is likely to be below 20%. In other words, we ve known for at least a decade that genetic influences on SSA are very little. 85
6 SSA studies based on twin registers, in which twins are enrolled on a voluntary basis simply because they are twins, probably produce much less bias than the snowball system. However, concordant twins (particularly mz twins) from such a register may still be disproportionately represented: participation in surveys that use twin registry members is not compulsory for any twins, and concordant twins tend to over-volunteer. The extent of this bias is not well-known, but is probably minimal, as seen by comparison of the results for SSA in Kendler, Thornton, Gilman, and Kessler (2000) and Bailey, Dunne, and Martin (2000). The results for SSA in these studies were very similar, though the first was a unique unbiased national survey and the second was drawn from a twin registry. Population studies, such as those from the highly documented health systems of the Scandinavian countries, will capture all twins with no bias, but do not register sexual orientation per se. Even these studies still need special surveys with participants consent, which may again introduce bias through over-volunteering. Modern Twin Registry Studies of SSA Early twin registry studies contained such small numbers of twins that this paper concentrates instead on the major registry studies that have the largest samples. These large studies and their countries of origin include Buhrich, Bailey, and Martin (1991), Australia; Hershberger (1997), United States; Bailey, Dunne, and Martin (2000), Australia; Kendler, Thornton, Gilman, and Kessler (2000), United States; Bearman and Brueckner (2002), United States; Santtila, Sandnabba, Harlaar, Varjonen, Alanko, and von der Pahlen (2008), Finland; Langstrom, Rahman, Carlstrom, and Lichtenstein (2010), Sweden; and Alanko, Santtila, Harlaar, Witting, Varjonen, Jern, Johansson, von der Pahlen, and Sandnabba (2010), Finland. It is now common to find studies of a few thousand pairs of twins, and the last six referenced studies were generally individually larger than all the pre-2000 studies combined. Varying measures of SSA have been used. However, we now know that the errors are so large that it makes no difference whether a criterion of attraction, fantasy, or 86
7 behavior was used to establish SSA. As a result, no differentiation was attempted in the present paper. This paper emphasizes what has been implicit for some time: SSA follows the same general pattern seen in many other traits (Turkheimer, 2000) in which genetic factors are significant but modest; postnatal factors affecting both twins (such as upbringing) are apparently less important (quite often close to zero influence); and nonshared factors (usually described as nonshared environmental factors) are usually more important than either and usually more than 50% of total variance (=influences, approximately), meaning nonshared factors generally have a moderate to strong effect. Psychologists reacted with frank disbelief and hostility to assertions in general twin studies that family influence was usually found to be so small, because their clinical experience with individuals unequivocally showed the opposite. Individuals they met were deeply affected by various unusual events in their histories. The conflict arose because the samples studied by each group were very different. Highly self-selected individuals in clinics have characteristics of those at one extreme end of a continuum, but prevalence of those characteristics often bears little relation to that of a carefully selected population-based sociological sample. Both conclusions, though conflicting, are therefore correct for their two samples, which consist of either the whole population or individuals (Whitehead, 1996). As described in that paper, clinical studies give unprecedented detail about individual psychological mechanisms that certainly occurred in the small sample described. On the other hand, surveys give a grand mean; the mechanisms revealed are often rather uninteresting and hide a wealth of significant detail. To some extent twin studies have fallen into the latter trap. However, another important resolution of the conflict was the discovery that children reacted to shared family factors in differing ways rather than in similar ways (Plomin & Daniels, 1987). Overwhelmingly, there is individualized reaction, so the observations of the clinicians are valid for those they are studying. But this also means that responses to shared experiences (in a family, for example) are mostly not shared. In 87
8 other words, sometimes two children in the same family respond differently to the same environment. Individual perceptions of experiences and subsequent responses to those experiences seem to be the key factor in the development of same-sex attractions. Results This paper does not use the rigorously random twin study by Kendler, Thornton, Gilman, and Kessler (2000), which though the result is much like the others had to combine results from men and women. Nor does it use the survey of adolescents by Bearman and Brueckner (2002), because among the adolescents there was a major SSA measurement problem and enormous variability from year to year (Igartua, Thombs, Burgos, & Montoro, 2009; Savin-Williams & Ream, 2007). The Santtila, Sandnabba, Harlaar, Varjonen, Alanko, and von der Pahlen (2008) survey was the largest, involving 2,334 pairs of twins. Like the second-largest survey by Langstrom, Rahman, Carlstro m, and Lichtenstein (2010), it used the Scandinavian health records, ensuring a relatively unbiased sample. Results: Calculated Genetic Fractions The mean in figure 1 for men is (22± 20)% where the error is the standard deviation. It made no statistical difference whether this was recalculated restricting the results to attraction or behavior. All surveys were therefore pooled. The errors are very large. The standard error (a measure of how far the result is from zero) is 4%, so the result is far from zero and is real, but a 22% genetic fraction is considered weak. Conventionally in the twin literature, 25, 50, and 75% are considered weak, moderate, and strong, respectively, based on the inherent mathematical relationship, since 0 is no relationship and 100% is a relationship totally dominated by the genetics. A result between 25 and 50% is considered modest. 88
9 Percentage Mean 10 0 Buhrich91 Hershberger97(1) Hershberger97(2) Hershberger97(3) Hershberger97(4) Bailey00 Kirk00(1) Kirk00(2) Kirk00(3) Kirk00(4) Kirk00(5) Kirk00(6) Kirk00(7) Santtila08(1) Santtila08(2) Langstrom10(1) Langstrom10(2) Alanko10 Figure 1. Estimates of genetic contribution to male SSA by various measures. Typical 95% error bars for selected studies are given. Absence of a histogram bar means the numerical result was zero. References and measurement basis: Buhrich, Bailey, and Martin (1991) Attraction+fantasy+contacts. Hershberger (1997)(1) Attractions when older than 25 years; (2) SSA partners when older than 25 years; (3) Sexual orientation (gay, bisexual, straight); (4) Same, but modeling included siblings. Bailey, Dunne, and Martin (2000) Sexual orientation: Kirk, Bailey, Dunne, and Martin (2000)(1) Same sex (SS) feelings now; (2) SS partners in last 12 months; (3) Fantasy; (4) Sexual orientation; (5) Attracted once or more over life to date; (6) Fantasy now (excitement or disgust at idea of SS contact); (7) SS partners over life to date; Santtila, Sandnabba, Harlaar, Varjonen, Alanko, and von der Pahlen (2008)(1) Potential to be SSinvolved (fantasy); (2) SS partners in last 12 months; Langstrom, Rahman, Carlstro m, and Lichtenstein, (2010)(1) Any lifetime SS partners; (2) SS partners over life to date; Alanko, Santtila, Harlaar, Witting, Varjonen, Jern, Johansson, von der Pahlen, and Sandnabba (2010) Attraction+partners normalized to degree of libido. 89
10 Percentage Mean Hershberger97(1) Hershberger97(2) Hershberger97(3) Hershberger97(4) Bailey00 Santtila08(1) Santtila08(2) Langstrom10(1) Langstrom10(2) Alanko10 Figure 2. Estimates of the genetic contribution to female SSA. References as for figure 1, plus Kirk, Martin, and Bailey (2000). The mean in figure 2 is (33 ±16)%, with a standard error of 5%. So a rough estimate of genetic contribution to female SSA is 33%. The result is far away from zero and is real, but its strength is only modest. The results from the different sets of investigators are generally about the same within error. But when compared with classical twin studies on other traits, the errors are alarmingly large a result that arises from the form of the statistical distribution of SSA in the population. Even with so many SSA studies, the statistical errors are still so large that there is no statistically significant difference between the two percentages for men and women. The mean figures for the genetic content for men and women 22% and 33%, respectively are still subject to the problems described later in the technical appendix, which will point out they are maxima and almost certain to reduce with further research. 90
11 Shared environmental factors in the studies cannot be distinguished from zero and are not graphed here. This is probably an illusion, as implied previously; in twin studies they often contribute to nonshared environmental effects. Results: Nonshared Environmental Effects In contrast, the errors on nonshared environmental fractions are much smaller. Figures 3 and 4 show the nonshared environmental fraction of SSA Percentage Mean Buhrich91 Hershberger97(1) Hershberger97(2) Hershberger97(3) Hershberger97(4) Bailey00 Kirk00(1) Kirk00(2) Kirk00(3) Kirk00(4) Kirk00(5) Kirk00(6) Kirk00(7) Santtila08(1) Santtila08(2) Langstrom10(1) Langstrom10(2) Alanko10 Figure 3. Nonshared environmental fraction for male SSA. The Hershberger (4) result is not missing, but is zero. Error bars are 95% confidence intervals, not available for the early studies. References as for figure 1. The mean is (64±14)% and the relative standard deviation is much lower than for the genetic fraction estimations. This is a moderately precise estimation. 91
12 90 80 Percentage Mean Hershberger97(1) Hershberger97(2) Hershberger97(3) Hershberger97(4) Bailey00 Santtila08(1) Santtila08(2) Langstrom10(1) Langstrom10(2) Alanko10 Figure 4. Nonshared environmental fraction from twin studies for females. References and same scale as for figure 2. (The Hershberger paper does not have female data for nonshared environment, only data for the genetic fraction). The mean is (63±12)%, statistically the same as for the males. Discussion The relatively low results for the genetic fraction are in huge contrast to the genetically programmed events of puberty. Twin studies put the very strong genetic influence on pubertal events at 90% (Silventoinen, Haukka, Dunkel, Tynelius, & Rasmussen, 2008). This is much higher than the 22% and 33% means for SSA. The degree of any genetic programming must be much less for SSA than for puberty. The calculated nonshared environmental contribution at 63 to 64% is moderate to strong. It is likely to increase with further research. 92
13 What Comprises Nonshared Environment? From traditional twin studies, we therefore find in summary that SSA is predominantly (63%) produced by erratic, unique factors of a type that could affect one mz twin but not another. An important outcome of the studies, therefore, is that the nonshared environment fraction is always two to three times the genetic fraction and has much smaller errors. Shared environment fractions are very low, consistent with zero but, as mentioned, this paper suggests that varying reactions to shared environment are, in fact, very important to individuals. Nonshared environment is characteristically elusive because it is erratic. There are probably very many individualistic experiences and factors that are very difficult to capture in surveys, explaining why general research into nonshared environment has been so unproductive. Turkheimer (2000) cites research that since 1987 had only accounted for 2% of such effects. However, in their study of socially problematic behaviors, Rodgers, Rowe, and Li (1994) accounted for a much larger proportion; they ascribed nonshared environment to features of the home that were experienced differently, so some research has succeeded. Nonshared environment contains several components: (a) possible measurement error of SSA; (b) biological randomness; (c) differing random events affecting one mz twin but not the other; and (d) differing random psychological reactions. The measurement error of SSA in adults is probably much less than in psychiatric studies of twins, in which conditions can be hard to diagnose. The error is probably not a large proportion of the nonshared environmental fraction. There is some inherent randomness in gene expression. Gene expression is not a perfect clockwork-type system; it contains noise or variation in the expression of genes, depending on the circumstances or point in time (Bar-Even, Paulsson, Maheshri, Carmi, O Shea, Pilpel, & Barkai, 2006). There is also randomness introduced when the 93
14 chromosomes recombine after the meiosis that forms the ova and sperm (Coop, Wen, Ober, Pritchard, & Przeworski, 2008). Those recombination events can be imperfect, introducing random errors. This makes individual animals irreducibly different from each other; however, many researchers breed for uniformity and ensure that the environment is completely standardized. This effect has been known and puzzled about for many years. For example, breeding colonies of laboratory rats, however much inbred, always contain significantly variable-weight individuals. The same applies to cloned animals and, therefore, human twins. Other interesting mechanisms producing epigenetic differences within the category of randomness have become recently known; these involve environmental influences on genes and are considered further in the technical appendix. This biochemical-connected randomness is a contributor to that part of the variance considered to be nonshared environmental. We do not presently know how large a percentage this is. Some examples of differing random events that could influence one mz twin but not the other especially among males could include male sexual abuse, bullying, exposure to same-sex pornography, encounter with someone interested in same-sex experimentation, and bad experience during encounters with the opposite sex. In only a minority of individuals would any particular factor be a major reason for the development of SSA. In general, however, an unusual event particularly of a sexual nature has a formative effect that may outweigh routine years of other types of experience. The nonshared environment may occur when individual children react differently to the same family environment or dynamics. For example, identical twins react differently to the same classroom (Oliver, Pike, & Plomin, 2008). Bailey and Pillard (1995) found identical SSA nonconcordant twins differed in some perceptions of childhood. Identical twins could also misperceive family dynamics in different ways. 94
15 Judging by the low values for shared environment in twin studies generally, these differing reactions to the same environment could be the predominant contributor to the random fraction. All these random factors mean that it is likely each case of SSA will have an almost unique history, though some broadly common themes may be present. Choice as a Possible Factor Is deliberate personal choice one of the idiosyncratic, erratic factors involved in SSA? This seems very unlikely but is raised here mainly because it tends to be a possible issue associated with SSA when research results are discussed in the public arena. Most other twin study traits would not be given the same type of attention by the public. Whether choice has the usual adult meaning must be considered in relation to the age of first attraction. Many papers show that the mean age of first attraction to the same or opposite sex (with 1 sigma error) is 10.9±4.5y for same-sex attraction and a similar 10.3±4.8y for opposite sex attraction (Hamer, Hu, Magnuson, Hu, & Pattatucci, 1993; Whitam & Mathy, 1986; D Augelli, Grossman, Salter, Vasey, Starks, & Sinclair, 2005; Floyd & Bakeman, 2006; Floyd & Stein, 2002; Grossman, 2008). The standard deviation is exceptionally wide, and programmed biological events have a significantly smaller standard deviation (paper in preparation). When the referenced studies were published at the end of the twentieth century, first attraction to the same or opposite sex preceded puberty by nearly two years. Subsequent to puberty, attraction becomes more clearly sexualized, and identification as GLB usually occurs during adolescence. Deliberate choices about sexual preference prior to ten years are probably quite erratic and immature. Even when clear choice is involved as an adult, there is evidence that random factors can be more important than the genetic elements. Thus in studies of opposite sex 95
16 attraction (OSA) mate selection and similarities in chosen partners, the genetic influence on mate characteristics was 34% genetic and 54% due to random factors the familiar pattern in behavioral genetics (Philippe & Ann, 2005). One can easily imagine that there could be a significant degree of chance in finding a mate who is personally attractive. Even in this case, choice is overshadowed by chance. Another paper studying OSA concluded that the genetic component to most preferred love styles or forms of romantic attraction was zero, that there was a small to modest contribution from the shared environment, and that there was an overwhelmingly large contribution from the nonshared environment, ranging between 61 and 85% (Waller & Shaver, 1994). In both of these papers that examined choice, the nonshared environment was predominant. Mate selection is probably one of the strongest examples of deliberate choice among life decisions but, as seen above, even it has a strong random component. For children, the idea of such deliberate choice is even less applicable. It is hard to think of any major life decision that is made involving informed choice at the age of ten. Although cases probably exist, it must be very rare to find any individual who makes a conscious choice about SSA or OSA at that age and who can describe the event and process later. Contrast that to most adults, who can describe clearly the decision to live with a partner. This means that the unique factors rather than deliberate choice must be strongest among children. The universal experience of those with SSA is that they neither deliberately chose it nor initially welcomed it; indeed, SSA is a significant factor in early suicide attempts. Similarly, the experience of those with OSA is that they did not deliberately choose it, in any common-sense use of the term choice, but merely reacted to life s circumstances in ways that seemed best at the time. According to Bailey (1995, p. 103), The argument over whether homosexuality is biological or freely chosen is perhaps the most common and the least productive version of the biology debate. The current analysis strongly backs his conclusion because it emphasizes the predominance of idiosyncratic factors over both. 96
17 Three Further Implications of Low Genetic Influence of SSA There are three further implications showing that genetics have a low influence in SSA. First, as demonstrated from the twin studies, SSA is unusually subject to production by erratic nonshared factors. The genetic fraction is much lower than usual compared with those for other traits; for example, a psychological component is typically nearer to but less than 50%. The high level of erratic nonshared factors for SSA is completely contrary to the common but uninformed assumption that SSA is usually produced by some inexorable deterministic process. This is exemplified by the anecdote of the nonconcordant mz twin pair in which the SSA twin insisted SSA must have a genetic origin (Bailey, 1995). Second, the twin data sum up the influences of all shared and erratic factors, whether presently known or not. After more than seven large studies, the concordance percentages and estimated contributions to genetic, shared, and nonshared influences as estimated by traditional twin-study methods are not likely to change by large factors. Thus it is almost impossible that some genetic or shared social factor whether already known or to be discovered in the future will be shown to be a predominant cause of SSA for the general population. As an illustration of this, it is emphasized that all genetic and social factors together produce for male mz twins a low 11% pairwise concordance (Bailey, Dunne, & Martin, 2000). All such shared factors must be individually classified as relatively weak or modest influences, especially if there are more than one. This must be the ultimate conclusion of all the various pieces of research currently being undertaken. All these are interesting, but will not find a predominant cause. We have that conclusion already: nonshared factors predominate. Third, the low results for the influence attributed to the shared environment leads to the conclusion that parental factors common to each twin are mostly not responsible in other words, parents are unwise to hold themselves directly responsible for SSA in a 97
18 child. Instead, SSA has usually arisen from idiosyncratic immature reactions to factors (including family factors) that are shared by all children. The nonshared factors seem to include the child s perceptions of his/her experiences and his/her individual reactions to those experiences. One conclusion of the study of Bell, Weinberg, and Hammersmith (1981) was that 70% of SSA variation was not accounted for by social factors. The present paper concludes that a similar fraction is random factors, but concealing varying reactions to shared social factors. Otis & Skinner (2004) studied which developmental factors had at least some perceived importance to those with SSA. Most participants were able to endorse at least part of one or more factors from a preselected list, generally of the type used by Bell, Weinberg, and Hammersmith (1981). The survey suggests that many respondents thought multiple causes could be involved. Modern investigations of genetic contributions to psychological traits show that many genes are involved, each with a very small contribution. It seems likely that the random contributions to SSA will likewise be multitudinous, and that each will have a small effect (although some may have a strong effect in some individuals). Conclusions The title of this paper asserted that neither genes nor (deliberate) choice was directly responsible for SSA. Chance incidents and idiosyncratic personal reactions predominate, and this has been demonstrated in almost all the twin surveys that have used modern sampling techniques. The present weak to modest estimates of 22% for men and 33% for women for all shared prenatal biological influences are likely to decrease significantly with further research (see technical appendix). The present fairly strong estimate of 63% for both men and women for the nonshared influences is correspondingly likely to increase with further research. The statement of LeVay (2010) derived from twin studies saying that genes exert a significant although not all-dominating influence 98
19 on sexual orientation (p. xv) must be interpreted as meaning the lower part of the significance range. Because of the calculated low genetic fraction, we are safe in saying that people are predominantly not born that way ; in fact, SSA is a good example of relative lack of prenatal preprogramming. However, the basic attraction constituent of SSA is on average present or absent at age ten, and explanations of origin should concentrate on ages earlier in childhood but post-natal. Some development and sexualization of this attraction certainly occurs at later ages. There has been, and still is, much research on prenatal causes for SSA. This is reasonable research in its own terms, but according to the twin data in this paper, any findings capable of impacting two identical twins similarly will be numerically minor in terms of total causes. SSA also seems usually not a matter of deliberate choice, because differing reactions to shared environment occur too young; immature reactions are much more erratic and varied than informed adult ones. Many years ago, Kinsey and associates said that it is possible that the early initiation of sexual experimentation with a same-gender partner is essentially a random event (Kinsey, Reichert, Cauldwell, & Mozes, 1955, as cited in Bickham, O Keefe, Baker, Berhie, Kommor, & Harper-Dorton, 2007). He may have been right. 99
20 Acknowledgment The author expresses gratitude to Professor Masaharu Hoshi and staff of the Research Institute of Radiation Biology and Medicine at Hiroshima University for hospitality and support during a number of visiting professorships from 2005 to Technical Appendix This appendix contains discussion of factors that are often highly technical but are an important part of the intellectual debate and will become more so. They tend to argue that the conclusions in the main body of the paper are quite conservative. Epigenetics Epigenetics is an emerging research current that describes how the environment influences gene expression. It is simply incorrect that genes control human characteristics in a deterministic, autonomous fashion. This has a potential impact on the twin studies described in the main text. It has been shown that gene expression is only 4% different in mz human twins near birth; more significant divergence emerges later due to epigenetic effects (Fraga, Ballestar, Paz, Ropero, Setien, Ballestar,... Esteller, 2005). Differences are more significant by age five (Mill et al., 2006) and continue to increase to old age by a factor of about 4. These epigenetic effects could contribute to different SSA outcomes, but those different SSA outcomes would mainly occur postnatally, when the environment is an actively contributing factor. These differences would decrease any effects of genetic preprogramming. The Assumptions of Twin Study Analysis There are rules for twin studies, and violating them leads in almost all cases to a genetic component that is too high. This paper asserts that the rules are often violated in SSA twin studies, resulting in genetic fractions that are significantly overestimated. This 100
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The Second Battle of Minette was an armed engagement between the Manticoran Alliance forces and the People's Navy, in which the Manticoran Alliance joint task force defeated the People's Navy Task Force 30 and took back the Minette System. (HH7)
Prelude Edit
Minette was taken by the Havenites in the First Battle of Minette as part of Operation Stalking Horse. (HH5)
Order of battle Edit
Manticoran Alliance Edit
Joined task force:
- a battle squadron, CO Admiral Henries
- Battle Squadron 2 (GSN), CO Admiral Wesley Matthews
The exact strength of the allied joint task force is not certain due to possible losses in the Battle of Candor, and because a picket of indeterminate size may have been left there. On the other hand, Task Force Minnette-01 and some forces from Task Force Grendelsbane joined[1].
Task Force 30:
- Battle Squadron 7 (PN)
- Battle Squadron 12 (PN)
- a battlecruiser squadron
- a screening element[2]
References Edit
|Operations of the
First Havenite-Manticoran War
|Battles of the
First Havenite-Manticoran War


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Journal of the American College of Cardiology
Universal Screening for Familial Hypercholesterolemia in Children
Author + information
- Received April 21, 2015
- Revision received June 8, 2015
- Accepted July 2, 2015
- Published online September 15, 2015.
Author Information
- Gašper Klančar, BSc∗,†,
- Urh Grošelj, MD∗,
- Jernej Kovač, PhD†,
- Nevenka Bratanič, MD∗,
- Nataša Bratina, MD∗,
- Katarina Trebušak Podkrajšek, PhD†,‡ and
- Tadej Battelino, MD∗,§∗ (tadej.battelino{at}mf.uni-lj.si)
- ∗Department of Pediatric Endocrinology, Diabetes and Metabolic Diseases, University Children's Hospital, UMC Ljubljana, Ljubljana, Slovenia
- †Unit of Special Laboratory Diagnostics, University Children's Hospital, UMC Ljubljana, Ljubljana, Slovenia
- ‡Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
- §Department of Pediatrics, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
- ↵∗Reprint requests and correspondence:
Dr. Tadej Battelino, University Children's Hospital, Department of Pediatric Endocrinology, Diabetes and Metabolic Diseases, Bohoričeva 20, SI-1000 Ljubljana, Slovenia.
Background Individuals with familial hypercholesterolemia (FH) who are untreated have up to 100-fold elevated risk for cardiovascular complications compared with those who are unaffected. Data for identification of FH with a universal screening for hypercholesterolemia in children are lacking.
Objectives This study sought genetic identification of FH from a cohort of children with elevated serum total cholesterol (TC) concentration, detected in a national universal screening for hypercholesterolemia.
Methods Slovenian children born between 1989 and 2009 (n = 272) with TC >6 mmol/l (231.7 mg/dl) or >5 mmol/l (193.1 mg/dl) plus a family history positive for premature cardiovascular complications, identified in a national universal screening for hypercholesterolemia at 5 years of age were genotyped for variants in LDLR, PCSK9, APOB, and APOE.
Results Of the referred children, 57.0% carried disease-causing variants for FH: 38.6% in LDLR, 18.4% in APOB, and none in PCSK9. Nine novel disease-causing variants were identified, 8 in LDLR, and 1 in APOB. Of the remaining participants, 43.6% carried the APOE E4 isoform. Estimated detection rate of FH in the universal screening program from 2009 to 2013 was 53.6% (95% confidence interval [CI]: 34.5% to 72.8%), peaking in 2013 with an upper estimated detection rate of 96.3%. Variants in LDLR, APOB, or the APOE E4 isoform occurred in 48.6%, 60.0%, and 76.5%, respectively, of patients with a family history negative for cardiovascular complications.
Conclusions Most participants who were referred from a national database of universal screening results for hypercholesterolemia had genetically confirmed FH. Data for family history may not suffice for reliable identification of patients through selective and cascade screening.
Individuals with untreated familial hypercholesterolemia (FH) have up to 100-fold increased risk for developing atherosclerosis and cardiovascular disease in early adulthood compared with unaffected individuals (1). Early diagnosis and management reduce this risk (2,3). The prevalence of FH in the general population is estimated to be between 1 in 200 (4,5) and 1 in 500 (4). FH is an autosomal dominant disorder clinically diagnosed by elevated concentration of serum total cholesterol (TC) and/or low-density lipoprotein (LDL) cholesterol, possible family history of premature cardiovascular complications, possible presence of xanthomas and corneal arcus, and/or causative variants in genes implicated in FH (4,6). Such variants are found predominantly in the gene encoding the LDL receptor (LDLR), which binds and clears LDL particles from the blood (7). A few patients have a common disease-causing variant of apolipoprotein B (APOB), p.Arg3527Gln, or disease-causing variants in the proprotein convertase subtilisin/kexin type 9 (PCSK9) gene (8). APOB is an integral component of LDL particle and a ligand for the LDL receptor (9), whereas PCSK9 regulates LDL receptor membrane concentration (10). Additionally, the interaction of common small-effect LDL cholesterol-elevating alleles in various genes may contribute to multifactorial disease development (11,12), with the apolipoprotein E (APOE) E4 isoform being the most recognized multivariant cause of hypercholesterolemia (13).
Various screening strategies have been proposed to identify children with FH. Only implementations of partial (14) and selective screenings primarily on the basis of family history are reported (15). These approaches lack the strength of identifying patients without known family history. Therefore, the National Heart, Lung, and Blood Institute (16), the National Lipid Association Expert Panel (17), and the European Expert Panel (15) proposed universal screening as a preferred method of screening for hypercholesterolemia in primary prevention efforts. Slovenia (population 2 million) started universal screening for hypercholesterolemia in 5-year-old children in 1995 (15). Screening was gradually implemented throughout the whole country (18), reaching an estimated majority of 5-year-old children (approximately 20,000) during 2013. Data for the efficacy of a national universal screening for detection of FH are lacking.
We sought to identify individuals with FH from a cohort with elevated serum TC levels detected in the Slovenian national universal screening for hypercholesterolemia in 5-year-old children.
Study population and design
Measurement of fasting serum TC was part of the national programmed routine examination of 5-year-old children by primary pediatricians (Slovenia national universal screening for hypercholesterolemia) (Central Illustration). According to national guidelines, participants with either a serum TC level of >6 mmol/l (231.7 mg/dl) without a family history of premature cardiovascular complications or with a TC level of >5 mmol/l (193.1 mg/dl) with a family history positive for premature cardiovascular complications (18) were referred after a consultation with their parents to a tertiary pediatric outpatient clinic. Data for participants' family histories were obtained in direct structured conversations with the parents. Participants' weight, body mass index, serum lipid profile (TC, LDL, high-density cholesterol [HDL], triglyceride [TG]), and whole-blood samples for targeted, next-generation sequencing (NGS) were obtained at the tertiary pediatric outpatient clinic. Simon Broome Register criteria (1) were used for assessment of family history. Positive family history was defined as myocardial infarction before 50 years of age in any second-degree relative or before 60 years of age in any first-degree relative or as TC >7.5 mmol/l (289.6 mg/dl) in any first- or second-degree relative (first-degree relation included parent, offspring or sibling; second-degree relation included grandparent, grandchild, nephew, niece, or half-sibling). Written informed consent was obtained from all parents or legal guardians. Principles of the Declaration of Helsinki were followed, and the Slovenian National Medical Ethics Committee approved the study (numbers 25/12/10 and 63/07/13).
DNA sequencing and analysis
Genomic DNA was isolated from whole-blood samples according to established laboratory protocols using FlexiGene isolation kit (Qiagen, Hilden, Germany). NGS is a high-throughput method based on simultaneous sequencing of numerous candidate genes or genomic intervals in a parallel fashion, effectively balancing cost and data quality for population-targeted sequencing studies (19). Samples for NGS were prepared following the manufacturer's protocol using ADH MASTR ready-to-use NGS-based molecular assay (Multiplicom NV, Niel, Belgium) for detection of variants in 4 genes associated with FH (encompassing coding and promoter regions of LDLR, PCSK9, APOE and part of APOB exon 26). Samples were sequenced using a MiSeq sequencer with MiSeq reagent kit version 2 (Illumina, San Diego, California) following the manufacturer's protocol, including recommendations for quality control parameters. The presence of copy number variations in LDLR was analyzed using NextGENe (Softgenetics, State College, Pennsylvania) and confirmed by Multiplex ligation-dependent probe amplification with an LDLR-P062 kit (MRC-Holland, Amsterdam, the Netherlands). Variants reported in disease-specific databases (20) and the Human Gene Mutation Database (HGMD) (Institute of Medical Genetics, School of Medicine, University of Cardiff, Cardiff, Wales) as unequivocally disease-causing were classified as pathogenic. In silico analysis of novel variants was performed with PolyPhen-2 (Harvard University, Cambridge, Massachusetts), SIFT (J. Craig Venter Institute, San Diego, California), and MutationTaster (University of Medicine, Berlin, Germany) bioinformatic tools. Variants declared to be disease-associated by at least 2 analytical algorithms were classified as novel causative variants. Single-nucleotide variants and small duplications/deletions with potentially disease-causing effect were confirmed by targeted Sanger DNA sequencing.
Statistical analysis
Descriptive statistics (means, standard deviations, and ratios) were used to characterize the investigated population. Assumption of equal proportions of detected FH population and total population enrolled in the national universal screening was made on the basis of the reported incidence, number of referred children, and number of live-born children publicly available at the Statistical Office of the Republic of Slovenia to estimate approximate number of children enrolled in the universal screening program in the previous 5 years (2009 to 2013), as exact data were not available. The detection rate of the universal screening in the studied population was evaluated by the number of children per generation referred to the tertiary outpatient clinic compared to the potential FH population estimated from the registry of live-born children and was reported as 1 in 500 and 1 in 200 incidence of FH (4,5). Data deviation from normal was evaluated with the D'Agostino and Pearson omnibus normality test. Differences in disease-associated variant accumulation between different groups of participants (sex and cardiovascular-positive family history), corresponding odds ratio (OR) and/or relative risk (RR), were evaluated using Fisher exact test for 2 × 2 contingency tables. Logistic regression model was applied (21) to calculate OR and RR with corresponding 95% confidence intervals (CIs). Genotype-associated differences among TC, LDL, HDL, and non-HDL levels and standard deviation score of body mass index were statistically evaluated using Kruskal-Wallis test with Dunn's multiple comparisons test. A p value <0.05 was used as an indicator of statistical significance. All statistical calculations were made in Prism version 6.01 software (GraphPad, Inc., La Jolla, California).
Altogether, 272 unrelated participants born between 1989 and 2009 were included in the study. Characteristics of participants are shown in Table 1. Serum TC levels at universal screening for hypercholesterolemia at age 5 and fasting lipid profile (TC, LDL, HDL, and TG levels) were measured at first admission to a tertiary pediatric outpatient clinic. Participants were referred to the tertiary pediatric outpatient clinic at 7.3 ± 3.1 years of age. A cardiovascular complications-positive family history according to Simone Broome Register criteria was identified in 33.1% of participants.
Prediction of national universal screening detection rate
The national universal screening in Slovenia was introduced gradually, and the referral rate to the tertiary institution reached its expected level only in 2013. An estimated 33,000 to 70,000 of 96,690 live-born children were enrolled at 5 years of age in the national universal screening from 2009 to 2013. Assuming an FH incidence of 1 in 500, the predicted detection rate from the data for the previous 5 years (2009 to 2013) was 53.6% (95% CI: 34.5% to 72.8%), reaching its peak in 2013 (children born in 2008) with an upper estimated detection rate of 96.3%. Assuming a greater incidence of 1 in 200, the upper estimated detection rate was only 38.5%.
Genetic characterization
Of 272 participants, 105 (38.6%) had heterozygous disease-causing variants in LDLR, 50 (18.4%) in APOB, and none in PCSK9. Twenty-three known (Online Table 1) and 8 novel disease-causing variants (Table 2) were identified in LDLR. Six novel disease-causing variants were missense and 2 were intronic. Four participants had multiple variants, 2 combinations of known disease-causing variants (Online Table 1) and 1 combination of a known and a novel disease-causing variant (Table 2). Copy number variations were identified in 3 patients, 2 had a deletion of exons 2 to 18, and 1 had a deletion of the whole LDLR coding region (Online Table 1). Two known missense variants (Online Table 1) and 1 novel disease-causing variant (Table 2) were identified in APOB. In the remaining participants without disease-causing variants, 51 (18.7%) were carriers of the hypercholesterolemia-associated APOE E4 isoform, whereas 66 participants (24.3%) had conditions that remained genetically undiagnosed (Table 1). A cardiovascular complication-negative family history according to Simone Broome Register criteria (1) was associated with 48.6%, 60.0%, and 76.5% of patients with disease-causing or disease-associated variants in LDLR, APOB, or APOE E4 isoform, respectively (Table 1). Relative risk of having a disease-causing genetic variant when a participant had a positive family history was 1.53 (RR: 1.529; 95% CI: 1.25 to 1.88; p = 0.0001). The OR for having a disease-causing genetic variant in participants with a TC level >6 mmol/l (231.7 mg/dl) was 7.71 compared with an OR of 7.71 (95% CI: 1.75 to 33.35; p = 0.0013) for the participants with TC levels between 5 and 6 mmol/l (193.1 and 231.7 mg/dl, respectively). Among 33 patients with TC levels between 5 and 6 mmol/l (193.1 and 231.7 mg/dl, respectively), 2 had disease-causing variants in LDLR and none in APOB. Among 177 patients with TC levels between 6 and 8 mmol/l (231.7 and 308.9 mg/dl, respectively), 31.1% had disease-causing variant in LDLR and 23.7% in APOB. Among 62 patients with a TC level >8 mmol/l (308.9 mg/dl), 77.4% had disease-causing variants in LDLR and 12.9% in APOB. Carriers of LDLR and APOB disease-causing genetic variants had on average higher TC levels at universal screening for hypercholesterolemia than noncarriers (7.7 ± 1.2 mmol/l vs. 6.6 ± 0.9 mmol/l, respectively [297.3 ± 46.3 mg/dl vs. 254.8 ± 34.8 mg/dl, respectively]; p < 0.0001). Additionally, carriers of LDLR and APOB disease-causing genetic variants had on average higher concentrations of TC (7.0 ± 1.1 mmol/l vs. 5.8 ± 0.8 mmol/l, respectively [272.0 ± 43.7 mg/dl vs. 222.4 ± 29.6 mg/dl, respectively]; p < 0.0001), LDL (5.2 ± 1.2 mmol/l vs. 3.8 ± 0.8 mmol/l, respectively [198.9 ± 45.5 mg/dl vs. 145.4 ± 29.1 mg/dl, respectively]; p < 0.0001), and non-HDL (5.6 ± 1.2 mmol/l vs. 4.3 ± 0.8 mmol/l, respectively [217.3 ± 45.0 mg/dl vs. 164.9 ± 31.3 mg/dl, respectively]; p < 0.0001) upon initial evaluation at the tertiary pediatric outpatient clinic than noncarriers. Associations among sex, serum TC levels, standard deviation score of body mass index, and presence of causative genetic variants in LDLR and APOB were not statistically significant.
This is the first study to evaluate genetic identification of FH by a national universal screening for hypercholesterolemia. Children were screened at 5 years of age, yet the mean referral age to the tertiary pediatric outpatient clinic was 7.3 years of age, indicating the requirement of additional educational intervention to promote more rapid referral of patients from primary care institutions for further clinical evaluation, along with a record of children not referred or whose parents refused referral. Serum TC level discriminates best between people with and without FH in the interval from 1 to 9 years of age, making it the optimal period for universal screening for hypercholesterolemia. Serum TC can identify 88.0% to 96.0% of cases, with a false positive rate between 0.1% and 1.0% (21). In addition, once an affected child is identified, 96.0% of parents with the disorder could be detected by identifying the parent with the higher cholesterol level (child–parent screening strategy) (22). All parents and older siblings from children identified as having FH in our study were referred for evaluation. The simulated detection rate of FH in our national universal screening for hypercholesterolemia on the basis of commonly reported incidence of 1 in 500 was more than 96.0% in the last year and allowed for a reliable identification of the risk population. Nevertheless, when an incidence rate of 1 in 200 is assumed, only 38.5% of the at-risk population was detected. An estimation of the total population enrolled in the national universal screening from 2009 to 2013 indicated that only approximately one-half of the total population was reached. Consequently, continuation and further improvements of screening and referral strategies will provide more data for the real FH incidence in the Slovenian population and improve clinical algorithms in FH risk management. The optimal age for a universal screening for hypercholesterolemia remains to be determined (15). Early dietary and lifestyle intervention along with cholestyramine assessment at 6 years of age (23) and use of statins after 8 years of age (24) in FH are beneficial, and therefore a diagnosis and intervention before pubertal age seems prudent (4,15,18).
A disease-causing genetic variant for FH was identified in 57% of participants referred from the universal screening, with an additional one-fifth identified with the most common multifactorial form of hypercholesterolemia, amounting to >75.0% of referred participants carrying a disease-causing or disease-associated genetic variant. Proportions of disease-causing variants in the present study were on the lower end of reported population data for LDLR and on the higher end in the same reports for APOB. For Czech (25), Polish (26), French (27), Spanish (28), and Italian (29) populations, the reported disease-causing variant frequencies were 23.9%, 45.0%, 73.9%, 96.4%, and 97.4%, respectively, and were 11.8%, 6.0%, 6.6%, 3.5%, and 2.2%, respectively, for APOB. Lack of the disease-causing PCSK9 variant in the Slovenian population was similar to that in the Finnish (30) and Greek (31) populations. The LDLR and APOB spectra of disease-causing variants are diverse. In large countries such as Italy (29), Spain (28), France (27), or Poland (25), more than 100 disease-causing variants contribute to a heterogeneous pool, whereas in populations such as those in Finland (30) or Iceland (32), the diversity of disease-causing variants is smaller, with less than 10 disease-causing variants present. Thirty-three disease-causing variants were identified in LDLR in the Slovenian cohort, 6 of which explained 55.2% of LDLR-positive cases. Two disease-causing variants were identified in APOB. One of these (p.Arg3527Gln) explained 96.0% of APOB-positive cases, probably due to its central European origin and a known migration patterns of carriers (33). Approximately 6.0% of disease-causing variants in LDLR and APOB were novel, confirming the wide variety of variants associated with the disease in other populations (4).
Almost one-fifth of the total cohort was negative for disease-causing variants in LDLR, APOB, and PCSK9 but carried the APOE E4 isoform, emphasizing the potential contribution of APOE genetic variants in the multifactorial cause of hypercholesterolemia (13). The remaining 24.3% of patients in the present study had no disease-causing or disease-associated variants identified, which is in accordance with other reports in which 10.0% to 40.0% (depending on the inclusion criteria) of those with clinical diagnosis of FH were found not to be carriers of disease-causing genetic variants in LDLR, APOB, or PCSK9 and were likely to have a polygenic or multifactorial type of hypercholesterolemia (28,34).
A significant advantage in cost reduction (approximately 3-fold decrease for the central European region) and timely identification of causative genetic variants (approximately 7-fold reduction in turnaround time in our laboratory) with the NGS compared with more widely used genetic screening methods (35) (e.g., denaturing high-pressure liquid chromatography or high resolution DNA melting analysis and Sanger sequencing) were observed. Moreover, NGS reduced the possibility of human errors due to reduced hands-on time per sample (36).
A 56.0% diagnostic yield and a significant association of tendon xanthoma and LDL-cholesterol level with the disease-causing LDLR or APOB variant has been demonstrated in an adult cohort (34). Comparable diagnostic yield in the adult population with clinical presentation of hypercholesterolemia (34) and our pediatric population without any clinical signs indicates that a universal screening may be an efficacious strategy for early detection of FH and prevention of cardiovascular complications. Importantly, almost one-half of participants with a TC level <6 mmol/l (231.7 mg/dl) carried a disease-causing or disease-associated genetic variant. Furthermore, a cardiovascular complications-negative family history according to Simone Broome Register criteria (1) was observed in one-half to three-quarters of patients with a disease-causing or disease-associated variant in LDLR, APOB, or the APOE E4 isoform. The RR of having a disease-causing variant with a positive family history was significant but relatively low. Data for a family history may not always be a reliable indicator for identification of potential FH patients (37).
Study limitations
This study was limited by a relatively small Slovenian population, as well as gradual implementation of the universal national screening for hypercholesterolemia. More data are required to optimize and evaluate the universal screening criteria and referral strategy. Additionally, a cascade screening for parents and siblings of identified affected children should be envisaged.
Results from the present study demonstrated for the first time that a national universal screening for hypercholesterolemia at 5 years of age identified genetically confirmed FH in more than one-half of the referred participants. Moreover, a genetic variant in APOE associated with hypercholesterolemia was detected in an additional one-fifth of the referred participants. Data for family history may not suffice for reliable identification of patients through selective screening. Our findings support the latest recommendations by professional forums for a universal screening for hypercholesterolemia in children. Coupled with a cascade screening for family members, universal screening for hypercholesterolemia could be a powerful approach for FH detection and prevention of cardiovascular complications. Additional studies are warranted to confirm the results of this study.
COMPETENCY IN SYSTEMS-BASED PRACTICE: Screening for hypercholesterolemia in children at 5 years of ages for familial hypercholesterolemia (FH) identified disease-causing variants in genes for LDLR and APOB in almost two-thirds of participants, and one-fifth were carriers of disease-associated variant encoding APOE E4 isoform. These data support proposals by the National Heart, Lung, and Blood Institute, National Lipid Association Expert Panel in the United States, and the European Expert Panel for universal screening as a preferred method of identifying FH as part of comprehensive primary prevention efforts.
TRANSLATIONAL OUTLOOK: Larger confirmatory studies are needed to determine the optimum timing and strategy for universal screening for FH using an expanded panel of FH-associated genes, and to define long-term efficacy and cost-effectiveness of this population-based approach.
The authors thank the participants in this study. They also thank the primary care pediatricians, the laboratory personnel, and the nursing team who helped in conducting the study.
This work was supported in part by Slovenian National Research Agency, Bleiweisova cesta 30, SI-1000 Ljubljana, Slovenia, grants P3-0343, J3-4116, J3-6800, and J3-6798. The authors have reported that they have no relationships relevant to the contents of this paper to disclose.
Listen to this manuscript's audio summary by JACC Editor-in-Chief Dr. Valentin Fuster.
- Abbreviations and Acronyms
- apolipoprotein B
- apolipoprotein E
- familial hypercholesterolemia
- high-density lipoprotein
- low-density lipoprotein
- low-density lipoprotein receptor
- next-generation sequencing
- proprotein convertase subtilisin/kexin type 9
- total cholesterol
- triglyceride
- Received April 21, 2015.
- Revision received June 8, 2015.
- Accepted July 2, 2015.
- American College of Cardiology Foundation
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- Scientific Steering Committee on behalf of the Simon Broome Register Group
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