A generalized Defries-Fulker regression framework for the analysis of twin data

A Twin Study of Altered White Matter Heritability in Youth With Autism Spectrum Disorder

OBJECTIVE

White matter alterations are frequently reported in autism spectrum disorder (ASD), yet the etiology is currently unknown. The objective of this investigation was to examine, for the first time, the impact of genetic and environmental factors on white matter microstructure in twins with ASD compared to control twins without ASD.

METHOD

Diffusion-weighted MRIs were obtained from same-sex twin pairs (6-15 years of age) in which at least 1 twin was diagnosed with ASD or neither twin exhibited a history of neurological or psychiatric disorders. Fractional anisotropy (FA) and mean diffusivity (MD) were examined across different white matter tracts in the brain, and statistical and twin modeling were completed to assess the proportion of variation associated with additive genetic (A) and common/shared (C) or unique (E) environmental factors. We also developed a novel Twin-Pair Difference Score analysis method that produces quantitative estimates of the genetic and environmental contributions to shared covariance between different brain and behavioral traits.

RESULTS

Good-quality data were available from 84 twin pairs, 50 ASD pairs (32 concordant for ASD [16 monozygotic; 16 dizygotic], 16 discordant for ASD [3 monozygotic; 13 dizygotic], and 2 pairs in which 1 twin had ASD and the other exhibited some subthreshold symptoms [1 monozygotic; 1 dizygotic]) and 34 control pairs (20 monozygotic; 14 dizygotic). Average FA and MD across the brain, respectively, were primarily genetically mediated in both control twins (A = 0.80, 95% CI [0.57, 1.02]; A = 0.80 [0.55, 1.04]) and twins concordant for having ASD (A = 0.71 [0.33, 1.09]; A = 0.84 [0.32,1.36]). However, there were also significant tract-specific differences between groups. For instance, genetic effects on commissural fibers were primarily associated with differences in general cognitive abilities and perhaps some diagnostic differences for ASD because Twin-Pair Difference-Score analysis indicated that genetic factors may have contributed to ∼40% to 50% of the covariation between IQ scores and FA of the corpus callosum. Conversely, the increased impact of environmental factors on some projection and association fibers were primarily associated with differences in symptom severity in twins with ASD; for example, our analyses suggested that unique environmental factors may have contributed to ∼10% to 20% of the covariation between autism-related symptom severity and FA of the cerebellar peduncles and external capsule.

CONCLUSION

White matter alterations in youth with ASD are associated with both genetic contributions and potentially increased vulnerability or responsivity to environmental influences.

DIVERSITY & INCLUSION STATEMENT

We worked to ensure sex and gender balance in the recruitment of human participants. We worked to ensure race, ethnic, and/or other types of diversity in the recruitment of human participants. We worked to ensure that the study questionnaires were prepared in an inclusive way. One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented racial and/or ethnic groups in science. One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented sexual and/or gender groups in science. One or more of the authors of this paper self-identifies as living with a disability. The author list of this paper includes contributors from the location and/or community where the research was conducted and they participated in the data collection, design, analysis, and/or interpretation of the work.

Heritability of Structural Patterning in the Human Cerebral Cortex

Genetic influences that govern the spatial patterning of the human cortex and its structural variability are still incompletely known. We analyzed structural MR images in twins, siblings, and pairs of unrelated subjects. A comprehensive set of methods was employed to quantify properties of cortical features at different spatial scales. Measures were used to assess the influence of genetic similarity on structural patterning. Results indicated that: (1) Genetic effects significantly influence all structural features assessed here at all spatial resolutions, albeit at different strengths. (2) While strong genetic effects were found at the whole-brain and hemisphere level, effects were weaker at the regional and vertex level, depending on the measure under study. (3) Besides cortical thickness, sulcal (geodesic) depth was found to be under strong genetic control. The local pattern indicated that two axes along (a) the anterior-posterior direction (insula to parieto-occipital sulcus), and (b) superior-inferior direction (central sulcus to callosal sulcus) presumably determine the segregation of four quadrants in each hemisphere early in development. (4) While strong structural asymmetries were found at the regional level, genetic influences on laterality were relatively minor.

Genetic and environmental influences on structural brain measures in twins with autism spectrum disorder

Atypical growth patterns of the brain have been previously reported in autism spectrum disorder (ASD) but these alterations are heterogeneous across individuals, which may be associated with the variable effects of genetic and environmental influences on brain development. Monozygotic (MZ) and dizygotic (DZ) twin pairs with and without ASD (aged 6-15 years) were recruited to participate in this study. T1-weighted MRIs (n = 164) were processed with FreeSurfer to evaluate structural brain measures. Intra-class correlations were examined within twin pairs and compared across diagnostic groups. ACE modeling was also completed. Structural brain measures, including cerebral and cerebellar gray matter (GM) and white matter (WM) volume, surface area, and cortical thickness, were primarily influenced by genetic factors in TD twins; however, mean curvature appeared to be primarily influenced by environmental factors. Similarly, genetic factors accounted for the majority of variation in brain size in twins with ASD, potentially to a larger extent regarding curvature and subcortical GM; however, there were also more environmental contributions in twins with ASD on some structural brain measures, such that cortical thickness and cerebellar WM volume were primarily influenced by environmental factors. These findings indicate potential neurobiological outcomes of the genetic and environmental risk factors that have been previously associated with ASD and, although preliminary, may help account for some of the previously outlined neurobiological heterogeneity across affected individuals. This is especially relevant regarding the role of genetic and environmental factors in the development of ASD, in which certain brain structures may be more sensitive to specific influences.

Outrageous fortune or destiny? Family influences on status achievement in the early life course

Psychologists using quantitative studies of the trait intelligence have established with much confidence that the impact of genes on intelligence increases with age, while the environmental effect of the family of origin declines. We examined the conjecture that a similar trend of increasing effect of genes/declining family environmental effect characterizes other status-related outcomes when arranged in typical age-graded sequence over adolescence and early adulthood. We used DeFries-Fulker (1985) (DF) analysis with longitudinal data on 1,576 pairs of variously-related young adult siblings (MZ twins; DZ twins; full siblings; half siblings; cousins; and nonrelated siblings; mean age 28) to estimate univariate quantitative genetic decompositions for fifteen status-related outcomes roughly ordered along the early life course: Verbal IQ, High school GPA, College plans, High school graduation, Some college, College graduation, Graduate school, Educational attainment, Occupational education, Occupational wages, Personal earnings, Household income, Household assets, Home ownership, and Subjective social status, with and without covariate controls for Age, Female gender, and Race/ethnicity (black, Hispanic, other; reference white). Results for successive outcomes did not support the conjecture of increasing heritability with maturity. Rather, the impacts of both the genes and the family environment tended to decline over the life course, resulting in a downward trend in family influences from all sources. There was some evidence of a recrudescence in relative influence of the family environment for outcomes related to the household that are often shared with a spouse, such as home ownership, suggesting a role of assortative mating in status reproduction. Other findings and limitations of the study are discussed.

P-values in genomics: apparent precision masks high uncertainty

Scientists often interpret P-values as measures of the relative strength of statistical findings. This is common practice in large-scale genomic studies where P-values are used to choose which of numerous hypothesis test results should be pursued in subsequent research. In this study, we examine P-value variability to assess the degree of certainty P-values provide. We develop prediction intervals for the P-value in a replication study given the P-value observed in an initial study. The intervals depend on the initial value of P and the ratio of sample sizes between the initial and replication studies, but not on the underlying effect size or initial sample size. The intervals are valid for most large-sample statistical tests in any context, and can be used in the presence of single or multiple tests. While P-values are highly variable, future P-value variability can be explicitly predicted based on a P-value from an initial study. The relative size of the replication and initial study is an important predictor of the P-value in a subsequent replication study. We provide a handy calculator implementing these results and apply them to a study of Alzheimer's disease and recent findings of the Cross-Disorder Group of the Psychiatric Genomics Consortium. This study suggests that overinterpretation of very significant, but highly variable, P-values is an important factor contributing to the unexpectedly high incidence of non-replication. Formal prediction intervals can also provide realistic interpretations and comparisons of P-values associated with different estimated effect sizes and sample sizes.

Comparison of the heritability of schizophrenia and endophenotypes in the COGS-1 family study

BACKGROUND

Twin and multiplex family studies have established significant heritability for schizophrenia (SZ), often summarized as 81%. The Consortium on the Genetics of Schizophrenia (COGS-1) family study was designed to deconstruct the genetic architecture of SZ using neurocognitive and neurophysiological endophenotypes, for which heritability estimates ranged from 18% to 50% (mean = 30%). This study assessed the heritability of SZ in these families to determine whether there is a "heritability gap" between the diagnosis and related endophenotypes.

METHODS

Nuclear families (N = 296) with a SZ proband, an unaffected sibling, and both parents (n = 1366 subjects; mean family size = 4.6) underwent comprehensive endophenotype and clinical characterization. The Family Interview for Genetic Studies was administered to all participants and used to obtain convergent psychiatric symptom information for additional first-degree relatives of interviewed subjects (N = 3304 subjects; mean family size = 11.2). Heritability estimates of psychotic disorders were computed for both nuclear and extended families.

RESULTS

The heritability of SZ was 31% and 44% for nuclear and extended families. The inclusion of bipolar disorder increased the heritability to 37% for the nuclear families. When major depression was added, heritability estimates dropped to 34% and 20% for nuclear and extended families, respectively.

CONCLUSIONS

Endophenotypes and psychotic disorders exhibit comparable levels of heritability in the COGS-1 family sample. The ascertainment of families with discordant sibpairs to increase endophenotypic contrast may underestimate diagnostic heritability relative to other studies. However, population-based studies also report significantly lower heritability estimates for SZ. Collectively, these findings support the importance of endophenotype-based strategies and the dimensional view of psychosis.

Heritability and the equal environments assumption: evidence from multiple samples of misclassified twins

Classically derived estimates of heritability from twin models have been plagued by the possibility of genetic-environmental covariance. Survey questions that attempt to measure directly the extent to which more genetically similar kin (such as monozygotic twins) also share more similar environmental conditions represent poor attempts to gauge a complex underlying phenomenon of GE-covariance. The present study exploits a natural experiment to address this issue: Self-misperception of twin zygosity in the National Longitudinal Survey of Adolescent Health (Add Health). Such twins were reared under one "environmental regime of similarity" while genetically belonging to another group, reversing the typical GE-covariance and allowing bounded estimates of heritability for a range of outcomes. In addition, we examine twins who were initially misclassified by survey assignment--a stricter standard--in three datasets: Add Health, the Minnesota Twin Family Study and the Child and Adolescent Twin Study in Sweden. Results are similar across approaches and datasets and largely support the validity of the equal environments assumption.