A Description of the FINRISK 1992 and 1997 Cohorts

<p>Compared to FINRISK-92, the FINRISK-97 cohort includes an additional sample of individuals aged 65–74 y. Numbers for this additional sample are described at the right-hand side for each endpoint. Persons examined refers to cohort individuals for whom information on smoking, blood pressure, cholesterol, and DNA, as well as consent for the use of DNA to study CHD and stroke, were available. Subcohorts are stratified random samples of the original cohorts including also cases. Mortality cases show total mortality, including also those who died from CHD or stroke. Thus, numbers in the boxes of subcohorts and outcome events are not mutually exclusive (see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.0020069#pgen-0020069-t001" target="_blank">Table 1</a>). F, females; M, males.</p

Clinical and metabolic characteristics of genotyped individuals.

<p>Clinical and metabolic characteristics of genotyped individuals.</p

Apolipoprotein E phenotypes, imputed haplotypes, and the carriers’ lipid profiles.

<p>Apolipoprotein E phenotypes, imputed haplotypes, and the carriers’ lipid profiles.</p

Enrichment of LDL-C or TG associated SNPs in FCH affected individuals by their frequency and effect on LDL-C and TG levels.

<p>Enrichment ratio is the ratio of the allele frequencies in the affected individuals (<i>n</i> = 234) to the allele frequencies in the Finnish FINRISK population cohort (<i>n</i> = 18,715). Only individuals without diabetes or other relevant confounders were included (<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006078#pgen.1006078.s001" target="_blank">S1 Text</a>). Under the null hypothesis of no enrichment, a 95% credible interval (shaded area) was estimated by calculating the enrichment statistic (enrichment ratio) for all variants with MAF > 0.001% across the genome excluding the loci of the 212 SNPs. Variants are designated as either lipid level elevating (red) or lowering (blue) for (a) LDL-C and (b) TG based on <i>β</i> estimates from linear regression in the FINRISK samples. Point size and color intensity reflect the magnitude of the effect. Only SNPs with at least one heterozygous carrier are shown <i>(n</i> = 194). *The enrichment ratio for <i>LPL</i> rs1801177 fell within the 95% credible interval.</p

Distributions of lipid levels in subsets of the Finnish general population and the FCH samples.

<p>Distributions of (a) LDL-C and (b) TG are shown for the Finnish FINRISK population cohort (FINRISK all, blue), hyperlipidemic Finnish population samples (FINRISK hyperlipidemic, green), all FCH family members (FCH all, brown), affected family members (FCH affected, red), and proband individuals (FCH probands, purple). Hyperlipidemia in the population samples is defined as TC or TG ≥ 90^th age- and sex-specific population percentile, analogously with the FCH diagnostic criteria. In (b) the x-axis is cut at 9 mmol/l. FCH, familial combined hyperlipidemia; FINRISK, The National FINRISK Study.</p

Positive and negative predictive values of high polygenic lipid scores.

<p>Positive and negative predictive values of high polygenic lipid scores.</p

Number of affected and unaffected individuals with high polygenic lipid scores or carriers of high-impact Mendelian variants.

<p>The black shading presents the number of (a) affected, and (b) unaffected individuals with high polygenic lipid scores (LDL-C, TG, or both polygenic scores over the 90^th percentile in the population) or carriers of a high-impact Mendelian variant (<i>APOE</i> ɛ2ɛ2, <i>n</i> = 2; or homozygosity for <i>APOA5</i> rs3135506). The families are sorted by the number of affected individuals with high polygenic lipid scores or a high-impact Mendelian variant in (a). The grey shading presents the number of other (a) affected, and (b) unaffected individuals in the family.</p

Number of affected individuals with high polygenic lipid score or Mendelian SNPs.

<p>Number of affected individuals with high polygenic lipid score or Mendelian SNPs.</p

Subsistence-level groups experiencing lifestyle change are a potential model for uncovering GxE interactions.

(A) Subsistence-level groups faced with urbanization, market integration, and modernization experience extreme variation in diet and physical activity levels, pathogen and toxin exposures, and social conditions. This list of environmental components for which there is extreme variation is not exhaustive and, in many cases, will also be population specific. We highlight a few broad categories that tend to change consistently during lifestyle transitions. Bidirectional arrows indicate factors that could either increase or decrease during urban transitions. (B) Studies such as The Turkana Health and Genomics Project [18,19], The Orang Asli Health and Lifeways Project [20], The Pacific Planetary Health Initiative, Madagascar Health and Environmental Research [21–23], The Tsimane Health and Life History Project [24], and The Shuar Health and Life History Project [25,26] all combine anthropological and biomedical data collection in transitioning societies and are thus poised to uncover GxE interactions in the context of evolutionary mismatch. We note that this list is meant to be illustrative and only includes projects directed by authors of this Essay; it does not by any means cover all of the rich and ongoing projects of small-scale, subsistence-level groups.</p

Mismatch diseases must be tested according to 3 criteria.

(A) Disease-related phenotypes must be more common or severe in the novel versus ancestral environment. We note that here we show mean differences in the phenotype between environments, but environmental effects could also impact trait variance. (B) These disease-related phenotypes must be attributable to an environmental variable, which will most often differ in mean and range between groups (e.g., physical activity influences cardiovascular health and is consistently higher in subsistence-level groups relative to individuals in postindustrial contexts). (C) It is necessary to establish a mechanism by which an environmental shift generates variation in disease-related phenotypes. At the genetic level, this could manifest as a locus for which a variant exhibits a past history of positive selection and is associated with health benefits in the ancestral environment but health detriments in the novel environment. A single locus with opposing effects is shown here for simplicity, but in reality, most complex traits will have highly polygenic architectures and diverse patterns of GxE interactions [34]. In panel C, horizontal lines represent haplotypes and the dark orange circle represents the selected variant. In all panels, dark blue represents the novel environment and light blue represents the ancestral environment.</p