Research and data

Genetics and age-related illnesses

brain showing signs of aging

Aging is a primary risk factor for Alzheimer’s disease as well as various heart and metabolic diseases, such as hypertension, hyperlipidemia, and diabetes. In the US, an estimated 5.8 million people age 65 and older are living with Alzheimer’s dementia and the number of people with the disease doubles every five years once beyond the age of 65. The burden of health care costs for Alzheimer’s is enormous, according to the Alzheimer’s Association. Early detection, treatment, and hopefully prevention of age-related diseases, should be public health priorities.

Looking to mitochondria for answers

Over the last decade, more evidence has linked aging to mitochondrial dysfunction. Mitochondria are tiny powerhouses in human cells. They generate more than 90% of the energy to support normal cellular functions, such as helping the body convert nutrients into energy and ensuring the body’s organs, systems, and tissue function properly. Mitochondria contain their own genetic material, the mitochondrial genome (mtDNA) that is exclusively inherited from a person’s mother. There are hundreds of thousands of mtDNA molecules in a human cell depending on its energy need. For example, there are up to several thousands of mtDNA copies in a heart cell because the heart constantly pumps blood to circulate through the body.

Researchers using special mice to study mtDNA and aging have increased mtDNA mutations contribute to premature aging and other observable characteristics, including progressive hair and hearing loss, spinal disorders, increased chances for heart disease, and reduced fertility. These mice studies have also shown that genetic mutations in mtDNA present at birth can speed aging and impair brain development.

In human observational studies, scientists found that reduced amount of mtDNA occurred in human spinal fluid at least a decade before Alzheimer’s symptoms develop.

Unlocking more mtDNA data

The functional impact of mtDNA in mice is likely to be different from that in humans and many unresolved questions remain within the field. Part of the challenge in studying the roles of mtDNA in the development of age-related diseases is that it is unethical to directly study modified mtDNA in the human body. It is also hard to pinpoint the harmful mtDNA because they are mixed with normal mtDNA molecules in our body and there can be hundreds of thousands of both normal and mutated molecules in one cell.

The National Institutes of Health and National Heart, Lung and Blood Institute, in an attempt to address the need for better data, launched the Trans-Omics for Precision Medicine (TOPMed) program. The goals is to sequence the human genome, including the mtDNA, in a large human study involving multiple races and age ranges. To date, more than 140,000 human genome have been sequenced. The TOPMed program has provided an unprecedented opportunity to further study mtDNA and how it relates to human age-related diseases.

At Boston University School of Public Health, this data was used to test our theory that aging damages mtDNA mutations, which in turn promotes age-related diseases. With funding from the NIH, we leveraged data from 65,000 participants from the US and UK to extensively measure cognitive brain structure and various health metrics related to heart disease. We believe that by understanding these links, we could ultimately be able to reduce age-related diseases and increase the quality of life, for a longer period.

Research confirms the mtDNA-aging link

Through our investigation, we found:

  • The average numbers of mtDNA somatic mutations stayed consistent in participants across a wide age range but became significantly greater in individuals 70-80 or older in European and Black or African American participants.
  • The proportion of harmful mtDNA mutations increase from young adulthood to older age.
  • The copies of mtDNA drastically decreased in older participants aged 65 and up, and this large decrease is at almost the same rate with every additional 10 years of age.
  • For younger participants under 65, there was not a strong relationship between age and amount of mtDNA molecules.

Our current research is exploring age-related traits, including metabolic traits and the global cognitive function that evaluate memory, learning abilities, concentration, and decision making. Through this work, we have found that an increase in mtDNA copies is associated with better global cognitive function in participants age 65 or older.

In another analysis of 52,000 participants of European descent, low amount of mtDNA molecules was associated with increased chances of obesity and hypertension, the risk of heart disease, stroke, type 2 diabetes, and several quantitative traits including increased body mass index, systolic blood pressure, fasting blood glucose and triglycerides. This was consistent with other race/ethnic origins. These findings suggests that insulin resistance underlies the relationship between decreasing mtDNA content, aging and metabolic diseases.

The overall findings of this research showing a decline in mtDNA content and increase in mutations in the older human population is important in our understanding of age-related diseases. Our on-going research will continue to focus on how changes in mtDNA to predict different age-related diseases and the relationship between mtDNA and genomics data, seeking answers that can hopefully lead to advancements in early detection and prevention in the coming years.

For more information about the work idea hub is doing to support innovation and collaboration, please contact us.

 

Dr. Chunyu Liu, PhD, is a research associate professor at Boston University School of Public Health. Her research is focused on evaluating risk factors for cardiovascular disease (CVD) including deciphering genes and identification of epigenetic factors, including mitochondrial DNA (mtDNA) genetics and in deep sequencing of heteroplasmic mutations and genome sequencing.

New call-to-action

You may also like

data analysis
In the news
Why Health Data Is Good Infrastructure

We need to strengthen and build robust health data utilities that can link and connect public health and clinical data systems. It makes sense to build these data utilities as public-private…

mental health and physical health are intrinsically tied together
Research and data
Mental health and physical health cannot be separated

The mind and body are deeply intertwined, and mental wellbeing is crucial for physical wellbeing. People with mental illness, such as depression, are at increased risk of chronic disease, such…

How machine learning helps identify people at high risk of suicide after discharge
Research and data
How Machine Learning Helps Predict Suicide After Discharge from Psychiatric Hospitalization

Suicide is a major public health problem, with approximately 800,000 suicide deaths globally each year. Thus, it’s crucial to accurately predict who will engage in suicidal behavior so that they…