A Biological Model of Acupuncture and its Derived Mathematical Modeling and Simulations

International audience(Aims) Acupuncture was employed since 2 millenaries, but the underlying mechanisms are not globally handled. The present study is aimed at proposing an explanation by pointing out involved processes and a convincing modeling to demonstrate its efficiency when carried out by trained practitioners. (Method) In the absence of global knowledge of any mechanism explaining the acupuncture process, a biological model is first developed, based on stimulation in a given domain around the needle tip of a proper mastocyte population by a mechanical stress, electrical, electromagnetic, or heat field. Whatever the type of mechanical or physical stimuli, mastocytes degranulate. Released messengers either facilitate the transfer of main mediators, or target their cognate receptors of local nerve terminals or after being conveyed by blood their receptors on cerebral cells. Signaling to the brain is fast by nervous impulses and delayed by circulating messengers that nevertheless distribute preferentially in the brain region of interest due to hyperemia. The process is self-sustained due to mastocyte chemotaxis from the nearby dense microcirculatory circuit and surrounding mastocyte pools, which are inadequate for acupuncture, but serve as a signal relay. A simple mathematical model is solved analytically. Numerical simulations are also carried out using the finite element method with mesh adaptivity. (Results) The analytical solution of the simple mathematical model demonstrates the conditions filled by a mastocyte population to operate efficiently. A theorem gives the blow-up condition. This analytical solution serves for validation of numerical experiments. Numerical simulations show that when the needle is positioned in the periphery of the acupoint or outside it, the response is too weak. This explains why a long training is necessary as the needle implantation requires a precision with a magnitude of the order of 1 mm. (Conclusion) The acupoint must contain a highly concentrated population of masto-cytes (e.g., very-high–amplitude, small-width Gaussian distribution) to get an initial proper response. Permanent signaling is provided by chemotaxis and continuous recruitment of mastocytes. Therefore, the density and distribution of mastocytes are crucial factors for efficient acupuncture as well as availability of circulating and neighboring pools of mastocytes

Trans-ethnic fine-mapping of genetic loci for body mass index in the diverse ancestral populations of the Population Architecture using Genomics and Epidemiology (PAGE) Study reveals evidence for multiple signals at established loci

Most body mass index (BMI) genetic loci have been identified in studies of primarily European ancestries. The effect of these loci in other racial/ethnic groups is less clear. Thus, we aimed to characterize the generalizability of 170 established BMI variants, or their proxies, to diverse US populations and trans-ethnically fine-map 36 BMI loci using a sample of >102,000 adults of African, Hispanic/Latino, Asian, European and American Indian/Alaskan Native descent from the Population Architecture using Genomics and Epidemiology Study. We performed linear regression of the natural log of BMI (18.5–70 kg/m2) on the additive single nucleotide polymorphisms (SNPs) at BMI loci on the MetaboChip (Illumina, Inc.), adjusting for age, sex, population stratification, study site, or relatedness. We then performed fixed-effect meta-analyses and a Bayesian trans-ethnic meta-analysis to empirically cluster by allele frequency differences. Finally, we approximated conditional and joint associations to test for the presence of secondary signals. We noted directional consistency with the previously reported risk alleles beyond what would have been expected by chance (binomial p < 0.05). Nearly, a quarter of the previously described BMI index SNPs and 29 of 36 densely-genotyped BMI loci on the MetaboChip replicated/generalized in trans-ethnic analyses. We observed multiple signals at nine loci, including the description of seven loci with novel multiple signals. This study supports the generalization of most common genetic loci to diverse ancestral populations and emphasizes the importance of dense multiethnic genomic data in refining the functional variation at genetic loci of interest and describing several loci with multiple underlying genetic variants

Whole genome sequence analyses of eGFR in 23,732 people representing multiple ancestries in the NHLBI trans-omics for precision medicine (TOPMed) consortium

Background: Genetic factors that influence kidney traits have been understudied for low frequency and ancestry-specific variants. Methods: We combined whole genome sequencing (WGS) data from 23,732 participants from 10 NHLBI Trans-Omics for Precision Medicine (TOPMed) Program multi-ethnic studies to identify novel loci for estimated glomerular filtration rate (eGFR). Participants included European, African, East Asian, and Hispanic ancestries. We applied linear mixed models using a genetic relationship matrix estimated from the WGS data and adjusted for age, sex, study, and ethnicity. Findings: When testing single variants, we identified three novel loci driven by low frequency variants more commonly observed in non-European ancestry (PRKAA2, rs180996919, minor allele frequency [MAF] 0.04%, P = 6.1 × 10−11; METTL8, rs116951054, MAF 0.09%, P = 4.5 × 10−9; and MATK, rs539182790, MAF 0.05%, P = 3.4 × 10−9). We also replicated two known loci for common variants (rs2461702, MAF=0.49, P = 1.2 × 10−9, nearest gene GATM, and rs71147340, MAF=0.34, P = 3.3 × 10−9, CDK12). Testing aggregated variants within a gene identified the MAF gene. A statistical approach based on local ancestry helped to identify replication samples for ancestry-specific variants. Interpretation: This study highlights challenges in studying variants influencing kidney traits that are low frequency in populations and more common in non-European ancestry

Rare coding variants in RCN3 are associated with blood pressure

Background: While large genome-wide association studies have identified nearly one thousand loci associated with variation in blood pressure, rare variant identification is still a challenge. In family-based cohorts, genome-wide linkage scans have been successful in identifying rare genetic variants for blood pressure. This study aims to identify low frequency and rare genetic variants within previously reported linkage regions on chromosomes 1 and 19 in African American families from the Trans-Omics for Precision Medicine (TOPMed) program. Genetic association analyses weighted by linkage evidence were completed with whole genome sequencing data within and across TOPMed ancestral groups consisting of 60,388 individuals of European, African, East Asian, Hispanic, and Samoan ancestries. Results: Associations of low frequency and rare variants in RCN3 and multiple other genes were observed for blood pressure traits in TOPMed samples. The association of low frequency and rare coding variants in RCN3 was further replicated in UK Biobank samples (N = 403,522), and reached genome-wide significance for diastolic blood pressure (p = 2.01 × 10− 7). Conclusions: Low frequency and rare variants in RCN3 contributes blood pressure variation. This study demonstrates that focusing association analyses in linkage regions greatly reduces multiple-testing burden and improves power to identify novel rare variants associated with blood pressure traits

Multi-ancestry transcriptome-wide association analyses yield insights into tobacco use biology and drug repurposing

Most transcriptome-wide association studies (TWASs) so far focus on European ancestry and lack diversity. To overcome this limitation, we aggregated genome-wide association study (GWAS) summary statistics, whole-genome sequences and expression quantitative trait locus (eQTL) data from diverse ancestries. We developed a new approach, TESLA (multi-ancestry integrative study using an optimal linear combination of association statistics), to integrate an eQTL dataset with a multi-ancestry GWAS. By exploiting shared phenotypic effects between ancestries and accommodating potential effect heterogeneities, TESLA improves power over other TWAS methods. When applied to tobacco use phenotypes, TESLA identified 273 new genes, up to 55% more compared with alternative TWAS methods. These hits and subsequent fine mapping using TESLA point to target genes with biological relevance. In silico drug-repurposing analyses highlight several drugs with known efficacy, including dextromethorphan and galantamine, and new drugs such as muscle relaxants that may be repurposed for treating nicotine addiction

Genetic determinants of telomere length from 109,122 ancestrally diverse whole-genome sequences in TOPMed

Genetic studies on telomere length are important for understanding age-related diseases. Prior GWASs for leukocyte TL have been limited to European and Asian populations. Here, we report the first sequencing-based association study for TL across ancestrally diverse individuals (European, African, Asian, and Hispanic/Latino) from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program. We used whole-genome sequencing (WGS) of whole blood for variant genotype calling and the bioinformatic estimation of telomere length in n = 109,122 individuals. We identified 59 sentinel variants (p < 5 × 10−9) in 36 loci associated with telomere length, including 20 newly associated loci (13 were replicated in external datasets). There was little evidence of effect size heterogeneity across populations. Fine-mapping at OBFC1 indicated that the independent signals colocalized with cell-type-specific eQTLs for OBFC1 (STN1). Using a multi-variant gene-based approach, we identified two genes newly implicated in telomere length, DCLRE1B (SNM1B) and PARN. In PheWAS, we demonstrated that our TL polygenic trait scores (PTSs) were associated with an increased risk of cancer-related phenotypes

Associations of autozygosity with a broad range of human phenotypes

In many species, the offspring of related parents suffer reduced reproductive success, a phenomenon known as inbreeding depression. In humans, the importance of this effect has remained unclear, partly because reproduction between close relatives is both rare and frequently associated with confounding social factors. Here, using genomic inbreeding coefficients (FROH) for >1.4 million individuals, we show that FROH is significantly associated (p < 0.0005) with apparently deleterious changes in 32 out of 100 traits analysed. These changes are associated with runs of homozygosity (ROH), but not with common variant homozygosity, suggesting that genetic variants associated with inbreeding depression are predominantly rare. The effect on fertility is striking: FROH equivalent to the offspring of first cousins is associated with a 55% decrease [95% CI 44–66%] in the odds of having children. Finally, the effects of FROH are confirmed within full-sibling pairs, where the variation in FROH is independent of all environmental confounding