Effective prevention of Alzheimer’s disease (AD) requires the development of risk prediction tools permitting preclinical intervention. We constructed a genetic risk score (GRS) comprising common genetic variants associated with AD, evaluated its association with incident AD and assessed its capacity to improve risk prediction over traditional models based on age, sex, education, and APOE ε4. In eight prospective cohorts included in the International Genomics of Alzheimer’s Project (IGAP), we derived weighted sum of risk alleles from the 19 top SNPs reported by the IGAP GWAS in participants aged 65 and older without prevalent dementia. Hazard ratios (HR) of incident AD were estimated in Cox models. Improvement in risk prediction was measured by the difference in C-index (Δ–C), the integrated discrimination improvement (IDI) and continuous net reclassification improvement (NRI>0). Overall, 19,687 participants at risk were included, of whom 2,782 developed AD. The GRS was associated with a 17% increase in AD risk (pooled HR = 1.17; 95%CI = [1.13–1.21] per standard deviation increase in GRS; p-value = 2.86 × 10−16). This association was stronger among persons with at least one APOE ε4 allele (HRGRS = 1.24; 95%CI = [1.15–1.34]) than in others (HRGRS = 1.13; 95%CI = [1.08–1.18]; pinteraction = 3.45 × 10−2). Risk prediction after seven years of follow-up showed a small improvement when adding the GRS to age, sex, APOE ε4, and education (Δ–Cindex = 0.0043 [0.0019–0.0067]). Similar patterns were observed for IDI and NRI>0. In conclusion, a risk score incorporating common genetic variation outside the APOE ε4 locus improved AD risk prediction and may facilitate risk stratification for prevention trials.

We assembled an ancestrally diverse collection of genome-wide association studies of type 2 diabetes (T2D) in 180,834 cases and 1,159,055 controls (48.9% non-European descent). We identified 277 loci at genome-wide significance (p<5x10-8), including 237 attaining a more stringent trans-ancestry threshold (p<5x10-9), which were delineated to 338 distinct association signals. Trans-ancestry meta-regression offered substantial enhancements to fine-mapping, with 58.6% of associations more precisely localised due to population diversity, and 54.4% of signals resolved to a single variant with >50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying foundations for functional investigations. Trans-ancestry genetic risk scores enhanced transferability across diverse populations, providing a step towards more effective clinical translation to improve global health.

Skull bone mineral density (SK-BMD) provides a suitable trait for the discovery of genes important to bone biology in general, and particularly for identifying components unique to intramembranous ossification, which cannot be captured at other skeletal sites. We assessed genetic determinants of SK-BMD in 43,800 individuals, identifying 59 genome-wide significant loci (4 novel), explaining 12.5% of its variance. Pathway and enrichment analyses of the association signals resulted in clustering within gene-sets involved in regulating the development of the skeleton; overexpressed in the musculoskeletal system; and enriched in enhancer and transcribed regions in osteoblasts. From the four novel loci (mapping to ZIC1, PRKAR1A, ATP6V1C1, GLRX3), two (ZIC1 and PRKAR1A) have previously been related to craniofacial developmental defects. Functional validation of skull development in zebrafish revealed abnormal cranial bone initiation that culminated in ectopic sutures and reduced BMD in mutated zic1 and atp6v1c1 fish and asymmetric bone growth and elevated BMD in mutated prkar1a fish. We confirmed a role of ZIC1 loss-of-function in suture patterning and discovered ATP6V1C1 gene associated with suture development. In light of the evidence presented suggesting that SK-BMD is genetically related to craniofacial abnormalities, our study opens new avenues to the understanding of the pathophysiology of craniofacial defects and towards the effective pharmacological treatment of bone diseases.

Several of the hypothesized or studied exposures that may affect dementia risk are known to increase the risk of death. This may explain counterintuitive results, where exposures that are known to be harmful for mortality risk sometimes seem protective for the risk of dementia. Authors have attempted to explain these counterintuitive results as biased, but the bias associated with a particular analytic method cannot be defined or assessed if the causal question is not explicitly specified. Indeed, we can consider several causal questions when competing events like death, which cannot be prevented by design, are present. Current dementia research guidelines have not explicitly considered what constitutes a meaningful causal question in this setting or, more generally, how this choice justifies and should drive particular analytic decisions. To contextualize current practices, we first perform a systematic review of the conduct and interpretation of longitudinal studies focused on dementia outcomes where death is a competing event. We then describe and demonstrate how to address different causal questions (referred here as "the total effect" and "the controlled direct effect") with traditional analytic approaches under explicit assumptions. Our application focuses on smoking cessation in late-midlife. To illustrate core concepts, we discuss this example both in terms of a hypothetical randomized trial and with an emulation of such a trial using observational data from the Rotterdam Study.

Migraine affects over a billion individuals worldwide but its genetic underpinning remains largely unknown. This genome-wide association study (GWAS) of 102,084 migraine cases and 771,257 controls identified 123 loci of which 86 are novel. The loci provide an opportunity to evaluate shared and distinct genetic components in the two main migraine subtypes: migraine with aura and migraine without aura. A stratification of the risk loci using 29,679 cases with subtype information, of which approximately half have never been used in a GWAS before, indicated three risk variants that appear specific for migraine with aura (in HMOX2, CACNA1A and MPPED2), two that appear specific for migraine without aura (near SPINK2 and near FECH), and nine that increase susceptibility for migraine regardless of subtype. The new risk loci include genes encoding recent migraine-specific drug targets, namely calcitonin gene-related peptide (CALCA/CALCB) and serotonin 1F receptor (HTR1F). Overall, genomic annotations among migraine-associated variants were enriched in both vascular and central nervous system tissue/cell types supporting unequivocally that neurovascular mechanisms underlie migraine pathophysiology.