Biology subjects

Kaplan, H.

Publications and source records attributed to Kaplan, H..

8 recordsLinked to original sources

bioRxiv2026

Comparison of lumbar paraspinal muscle size and density between members of the US Framingham Heart Study and Tsimane forager-horticulturalists of Bolivia

Paraspinal muscles support and move the spine, and reduced size and density of these muscles is associated with increased risk of vertebral fracture and back pain. We test the hypothesis that subsistence-oriented forager-horticulturalists (Bolivian Tsimane) have larger and denser paraspinal muscles, and smaller age-related differences in paraspinal muscle size and density, than more sedentary post-industrialized suburbanites (Framingham Heart Study [FHS]). We measured cross-sectional area (CSA) and density of trunk extensors and psoas major at L3 from computed tomography scans of 411 FHS and 330 Tsimane (50% women, aged 50-90 years). Sex-stratified linear regressions determined associations of muscle CSA and density with age and cohort (Tsimane or FHS [ref.]), with and without an age-cohort interaction term. Covariates were height and weight. After adjusting for covariates, Tsimane women had 11-14% larger and denser extensors, and 17-26% smaller and less-dense psoas major, than FHS women. Tsimane men had 8-21% smaller and less-dense psoas major than FHS men. The age-related difference in extensors density was 41% smaller for Tsimane men than for FHS men. There were no other significant age-related cohort differences in muscle CSA or density. We observed a different balance in the size and density of trunk extensors versus psoas major between Tsimane and FHS. A possible explanation for this observation is cohort differences in the amount and types of physical activity, although future work is required to determine the influence of lifestyle and environmental factors on paraspinal muscle size and density.

evolutionary biology↗

bioRxiv2026

Evaluating performance bias in face-to-BMI vision transformer models across diverse human populations

Computer vision models that estimate body mass index (BMI) from facial features offer a non-invasive, low-cost alternative to physical measurement, with uses in telemedicine, emergency care where a scale or measuring tools arent available, automated self-monitoring, and large-scale epidemiological research. Most of these models, however, are trained on government records, social media images, and celebrity photographs, sources that introduce dataset biases and fail to represent the general public. This study tests how well a face-to-BMI machine learning model generalizes across populations, specifically how morphological diversity and population-specific training data affect cross-cultural accuracy. We trained and evaluated Vision Transformer (ViT-H/14) models on paired BMI measurements and facial photographs from four Indigenous populations: the Orang Asli of Malaysia, the Ju/hoansi of Southern Africa, the Sama residing in the Philippines, and the Tsimane of Bolivia. To evaluate how training data composition affects predictions, we compared four training strategies, from single-population models (focal models) to models trained on the full combined global dataset (global models). In-distribution training always produced the best performance. Models exposed to a target populations morphology, whether focal or global, consistently predicted BMI most accurately for that population. But when a target population differed from the training sample, adding more cross-cultural variation to training improved out-of-distribution predictions. Therefore, training on a populations own data works best when that data exists, and training on data spanning a wide range of human morphology is the strongest fallback when it doesnt. These findings suggest that while target population training data produces the most accurate results, training on datasets that capture global morphological variation substantially improves performance in unrepresented populations. Broader diversity in training data is essential for developing machine learning health tools that generalize reliably across human populations.

bioinformatics↗

bioRxiv2025

Prehistoric Global Migration of Vanishing Gut Microbes With Humans

The gut microbiome is crucial for health and greatly affected by lifestyle. Many microbes common in non-industrialized populations are disappearing or extinct in industrialized populations. Understanding which microbes have been long-term residents of the human gut, and may have co-evolved with humans, has implications for the importance of microbial biodiversity loss for health. However, the genetic complexities of microbial evolution and the plasticity of gut microbiome composition have made it challenging to define these long-term associations. Here, we performed deep metagenomic sequencing of the Tsimane horticulturalists of Bolivia and compared their gut microbiomes with the Hadza hunter-gatherers of Tanzania. These two populations, whose ancestors were separated for tens of thousands of years, share 1,231 microbial species, most of which are absent in industrialized populations. Population genetic analyses in 636 of these shared species revealed patterns of microbial divergence and gene flow consistent with prehistoric human co-migration, with estimated split times that approximately align with human migration out of Africa and into the Americas. Our findings indicate that a diverse gut microbiome co-migrated with humans around the globe, persisting over millennia. However, many of these species are now vanishing in industrialized populations, and the consequences for human health remain uncertain.

microbiology↗

bioRxiv2024

Cost-effective solutions for high-throughput enzymatic DNA methylation sequencing

Characterizing DNA methylation patterns is important for addressing key questions in evolutionary biology, geroscience, and medical genomics. While costs are decreasing, whole-genome DNA methylation profiling remains prohibitively expensive for most population-scale studies, creating a need for cost-effective, reduced representation approaches (i.e., assays that rely on microarrays, enzyme digests, or sequence capture to target a subset of the genome). Most common whole genome and reduced representation techniques rely on bisulfite conversion, which can damage DNA resulting in DNA loss and sequencing biases. Enzymatic methyl sequencing (EM-seq) was recently proposed to overcome these issues, but thorough benchmarking of EM-seq combined with cost-effective, reduced representation strategies has not yet been performed. To do so, we optimized Targeted Methylation Sequencing protocol (TMS)--which profiles [~]4 million CpG sites--for miniaturization, flexibility, and multispecies use at a cost of [~]$80. First, we tested modifications to increase throughput and reduce cost, including increasing multiplexing, decreasing DNA input, and using enzymatic rather than mechanical fragmentation to prepare DNA. Second, we compared our optimized TMS protocol to commonly used techniques, specifically the Infinium MethylationEPIC BeadChip (n=55 paired samples) and whole genome bisulfite sequencing (n=6 paired samples). In both cases, we found strong agreement between technologies (R{superscript 2} = 0.97 and 0.99, respectively). Third, we tested the optimized TMS protocol in three non-human primate species (rhesus macaques, geladas, and capuchins). We captured a high percentage (mean=77.1%) of targeted CpG sites and produced methylation level estimates that agreed with those generated from reduced representation bisulfite sequencing (R{superscript 2} = 0.98). Finally, we applied our protocol to profile age-associated DNA methylation variation in two subsistence-level populations--the Tsimane of lowland Bolivia and the Orang Asli of Peninsular Malaysia--and found age-methylation patterns that were strikingly similar to those reported in high income cohorts, despite known differences in age-health relationships between lifestyle contexts. Altogether, our optimized TMS protocol will enable cost-effective, population-scale studies of genome-wide DNA methylation levels across human and non-human primate species.

genomics↗

bioRxiv2021

Helminth infection is associated with dampened cytokine responses to viral and bacterial stimulations in Tsimane hunter-horticulturalists.

BackgroundSoil-transmitted helminth (STH) infections can catalyze immunological changes that affect the response to subsequent infections, particularly those that elicit strong inflammatory responses. As globalization heightens the risk that remote communities with high STH prevalence will encounter novel pathogens, understanding how STHs shape immune responses to these downstream infections becomes increasingly crucial. MethodologyWe worked with Tsimane forager-horticulturalists in the Bolivian Amazon, where STHs are prevalent. We tested whether STHs and eosinophil levels--most likely indicative of infection in this population--are associated with dampened immune responses to in vitro stimulation with H1N1 and lipopolysaccharide (LPS) antigens. Whole blood samples (n = 179) were treated with H1N1 vaccine and LPS and assayed for 13 cytokines (interferon gamma [INF-{gamma}], interleukin [IL]-1{beta}, IL-2, IL-4, IL-5, IL-6, IL-7, IL-8, IL-10, IL-12p70, IL-13, Granulocyte-macrophage colony-stimulating factor [GM-CSF], and Tumor necrosis factor-alpha [TNF-]). We evaluated how STHs and eosinophil levels affected cytokine responses and T helper (Th) 1 and Th2-cytokine suite responses to stimulation. ResultsInfection with Ascaris lumbricoides was significantly (p [≤] 0.05) associated with lower response of some cytokines to H1N1 and LPS in women. Eosinophils were significantly negatively associated with some cytokine responses to H1N1 and LPS, with the strongest effects in women, and associated with a reduced Th1- and Th2-cytokine response to H1N1 and LPS in women and men. Conclusions and implicationsWe find that STHs were associated with dampened cytokine responses to certain viral and bacterial antigens, and suggest that this mitigation of host-induced damage may reduce the incidence of cytokine storms in populations with high STH prevalence.

immunology↗

bioRxiv2021

APOE4 is associated with elevated blood lipids and lower levels of innate immune biomarkers in a tropical Amerindian subsistence population

In post-industrial settings, APOE4 is associated with increased cardiovascular and neurological disease risk. However, the majority of human evolutionary history occurred in environments with higher pathogenic diversity and low cardiovascular risk. We hypothesize that in high-pathogen and energy-limited contexts, the APOE4 allele confers benefits by reducing baseline innate inflammation when uninfected, while maintaining higher lipid levels that buffer costs of immune activation during infection. Among Tsimane forager-farmers of Bolivia (N=1266), APOE4 is associated with 30% lower C-reactive protein, and higher total cholesterol and oxidized-LDL. Blood lipids were either not associated, or negatively associated with inflammatory biomarkers, except for associations of oxidized-LDL and inflammation which were limited to obese adults. Further, APOE4 carriers maintain higher levels of total and LDL cholesterol at low BMIs. These results suggest the relationship between APOE4 and lipids is likely beneficial for pathogen-driven immune responses, and unlikely to increase cardiovascular risk in an active subsistence population.

evolutionary biology↗

bioRxiv2020

Phage-Antibiotic Synergy Is Driven By A Unique Combination Of Antibacterial Mechanism Of Action And Stoichiometry

The continued rise in antibiotic resistance is precipitating a medical crisis. Bacteriophage (phage) has been hailed as one possible therapeutic option to augment the efficacy of antibiotics. However, only a handful of studies have addressed the synergistic relationship between phage and antibiotics. Here, we report a comprehensive analysis of phage-antibiotic interaction that evaluates synergism, additivism, and antagonism for all classes of antibiotics across clinically achievable stoichiometries. We combined an optically-based real-time microtiter plate readout with a matrix-like heatmap of treatment potencies to measure phage and antibiotic synergy (PAS), a process we term synography. Phage-antibiotic synography was performed against a pandemic drug-resistant clonal group of E. coli (ExPEC) with antibiotic levels blanketing the minimum inhibitor concentration (MIC) across seven orders of viral titers. Our results suggest that, under certain conditions, phages provide an adjuvating effect by lowering the MIC for drug-resistant strains. Furthermore, synergistic and antagonistic interactions are highly dependent on the mechanism of bacterial inhibition by the class of antibiotic paired to the phage, and when synergism is observed, it suppresses the emergence of resistant cells. Host conditions that simulate the infection environment, including serum and urine, suppress PAS in a bacterial growth-dependent manner. Lastly, phage burst size seems to be a significant driver of synergism. Collectively, this data suggests lytic phages can resuscitate an ineffective antibiotic for previously resistant bacteria, while also synergize with antibiotics in a class-dependent manner, processes that may be dampened by lower bacterial growth rates found in host environments. Significance StatementBacteriophage (phage) therapy is a promising approach to combat the rise of multi-drug resistant bacteria. Currently, the preferred clinical modality is to pair phage with an antibiotic, a practice thought to improve efficacy. However, antagonism between phage and antibiotics has been reported, the choice of phage and antibiotic is not often empirically determined, and the effect of the host factors on the effectiveness is unknown. Here, we interrogate phage-antibiotic interactions across antibiotics with different mechanisms of action. Our results suggest that phage can lower the working MIC for bacterial strains already resistant to the antibiotic, is dependent on the antibiotic class and stoichiometry of the pairing, and is dramatically influenced by the host microenvironment.

microbiology↗

bioRxiv2019

The Life History of Human Foraging: Cross-Cultural and Individual Variation

Human adaptation depends upon the integration of slow life history, complex production skills, and extensive sociality. Refining and testing models of the evolution of human life history and cultural learning will benefit from increasingly accurate measurement of knowledge, skills, and rates of production with age. We pursue this goal by inferring individual hunters of hunting skill gain and loss from approximately 23,000 hunting records generated by more than 1,800 individuals at 40 locations. The model provides an improved picture of ages of peak productivity as well as variation within and among ages. The data reveal an average age of peak productivity between 30 and 35 years of age, though high skill is maintained throughout much of adulthood. In addition, there is substantial variation both among individuals and sites. Within study sites, variation among individuals depends more upon heterogeneity in rates of decline than in rates of increase. This analysis sharpens questions about the co-evolution of human life history and cultural adaptation. It also demonstrates new statistical algorithms and models that expand the potential inferences drawn from detailed quantitative data collected in the field.

animal behavior and cognition↗