Scientists discover key age-related biological changes in 40s and 60s

In a recent study published in Nature Aging, researchers from Singapore and the US conducted a comprehensive longitudinal cohort profiling (n=108) using state-of-the-art multi-omics techniques to identify nonlinear dynamics of human aging. The study cohort included California residents aged 25 to 75 years, who were followed for up to 6.8 years (median 1.7 years).

The study found that only 6.6% of molecular markers showed linear changes with age, while a significant proportion – 81% – showed non-linear patterns, highlighting the complexity of the aging process. Analysis of molecular markers revealed that human aging is not a linear process, with dramatic disruptions in certain biological pathways observed around 44 and 60 years of age, such as alcohol and lipid metabolism at age 40 and carbohydrate metabolism and immune regulation at age 60. These findings provide unprecedented insight into the biological and molecular pathways associated with human aging and represent a significant step forward in identifying therapeutic interventions against age-related chronic diseases.

Aging is defined as the decline in physiological functions associated with age, which is associated with the risk and development of chronic diseases such as diabetes, neurodegeneration, cancer, and cardiovascular disease.

Recent studies using modern systems-based high-throughput omics technologies show that, contrary to previous beliefs, aging is not a linear process. The study used transcriptomics, proteomics, metabolomics, and microbiome analysis to explore the complexity of aging at the molecular level. Certain age thresholds may serve as key moments corresponding to significant nonlinear changes in metabolism and molecular profiles. For example, neurodegenerative diseases and cardiovascular diseases show significant peaks in prevalence in the population around 40 and 60 years of age.

Despite this relatively new knowledge, the literature has so far focused on the biology of aging, with the assumption that aging is a linear process. This approach may have obscured the mechanistic insights needed to develop therapeutic interventions against age-related diseases, hindering the achievement of prolonging human lifespan and health in old age.

The aim of this study was to address this gap in the literature by using a battery of deep multi-omics profiling methods to examine specific changes in biological and molecular pathways associated with different age groups of adults. The study was conducted on a cohort of healthy adult volunteers from California, USA, aged 25 to 75 years. Participants were eligible for the study with no clinical history of chronic diseases such as anemia, cardiovascular disease, cancer, psychiatric disorders, or bariatric surgery.

During baseline data collection, a modified insulin suppression test, fasting plasma glucose test, and hemoglobin A1C (HbA1C) test were performed to determine insulin resistance, diabetes, and average glucose levels in participants. In addition, participants' body mass index (BMI) was recorded at study entry and follow-up.

The study included 108 participants (51.9% women) aged 25 to 75 years (median 55.7). Participants provided samples for multi-omics data every 3-6 months (median follow-up was 1.7 years, maximum 6.8 years). This rigorous longitudinal analysis allowed the researchers to capture both linear and non-linear molecular changes associated with aging. The multi-omics results highlighted the importance of non-linear approaches to characterizing biological aging, showing that of the molecules examined, only 6.6% showed linear changes associated with age, while 81% showed non-linear patterns.

These molecular patterns were remarkably consistent across all seven multi-omics studies, suggesting profound biological implications. A trajectory clustering approach used to group molecules by their temporal similarity revealed the presence of three distinct clusters (clusters 5, 2, and 4).

The first included a transcriptomics module related to mRNA and autophagy, which showed a sharp increase around age 60. This pathway maintains cellular homeostasis and demonstrates an increased risk of diseases associated with aging. The second cluster included the phenylalanine metabolism pathway, covering serum/plasma glucose levels and blood urea nitrogen levels, which increase significantly around age 60, indicating a decline in kidney function and an increased risk of cardiovascular disease. The third cluster included pathways related to caffeine metabolism and unsaturated fatty acid biosynthesis, which are important for cardiovascular health.

To better understand the peaks of microbiome and molecule dysregulation during aging, the researchers used a modified differential expression sliding window analysis (DE-SWAN) algorithm. The results of the analysis highlight the presence of two distinct peaks (ridges) corresponding to ages around 40 and 60 years, which was consistent across all multi-omics profiles (especially proteomics). Modules of the first peak were closely associated with alcohol and lipid metabolism, while modules of the second peak were associated with immune system disorders, kidney function, and carbohydrate metabolism.

The present study highlights the highly nonlinear nature of biological and molecular processes associated with human aging, as demonstrated in seven different multi-omics studies. The study is notable in that it further identifies specific patterns in the aging process that increase sharply around 40 and 60 years of age, corresponding to biologically significant dysregulation of alcohol and lipid metabolism (at 40 years of age) and immune dysfunction, renal function, and carbohydrate metabolism (at 60 years of age).

“These rich multi-omics data and approach provide a deeper understanding of the complex processes of aging, which we believe adds value to existing research. However, further studies are needed to validate and expand on these findings, perhaps using larger cohorts to capture the full complexity of aging.”