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Congratulations, Cecilia Lindgren…

Picture of Cecilia Lindgren
Cecilia Lindgren, new director of the Big Data Institute, works a lot on willpower: “You can’t control everything, but if you have the will, you can find solutions.”

…a Lund University alumna who has taken a new position as director of the Big Data Institute in Oxford!

“Thank you! I am thrilled about this”, says Cecilia Lindgren.

She describes her new role as Director of the Big Data Institute (BDI) as a new chapter, but a continuation of something in which she is strongly rooted. Ever since she completed her PhD at Lund University, she has used Big Data in her research in various ways, interweaving medical knowledge and biological insight with computer science and statistics.

Cecilia Lindgren’s own research addresses the distribution of fat around the body and what causes some people who are obese to suffer from diabetes while others do not. These are complex and difficult connections, affected by both environment and genes.

“In the beginning, we thought we would find a single gene that causes the distribution of fat or type 2 diabetes. But as it turned out, there are many different genetic variations which, in turn, are affected by complex, environmental factors.”

Lund is a perfect mix

Cecilia Lindgren began her research as a doctoral student under Leif Groop – “my scientific grandfather as she calls him – and remembers how he ensured that the doctoral students got a chance to rotate amongst the patients in the endocrinology ward. But the clinical life was not something that attracted Cecilia.

“I am driven by intuition and realised quickly that I was too sensitive to work clinically with patients. However, Leif gave me a profound respect and enthusiasm for maintaining the medical keel in my research.”

She refers to her time in Lund as “a perfect mix of cutting-edge research and student fun”.

One of her lecturers was Mikael Dolsten who played a key role in producing the Pfizer/BioNTech vaccine, but Cecilia Lindgren fondly mentions many people from the time who meant a lot to her: Erik Renström, Marju Orho-Melander, Henrik Mulder and Cecilia Holm, to mention a few.

“It was fantastic to study and conduct research in Lund, because research is creative. You need to take breaks, get inspiration and find new opportunities beyond your immediate workplace. And there were many opportunities to be had in Lund.”

She speaks warmly of the Gothenburg student nation and the Botanical Garden.

“And every time something went well, I celebrated at the Grand Hotel. I am proud of my half-Scanian roots and I have a summer house in Österlen to which I return.”

Translating research into clinical benefit

Cecilia Lindgren has been part of the change and explosion of the field abreast of technological development. During her inaugural lecture as a new professor in 2018, she spoke about her involvement in conducting a comprehensive association study, known as a GWAS, in Oxford in 2007. GWAS is a method used to find out which genetic variants are involved in various diseases and entails comparing the genetic material of a large group of people to identify variations between those who have a disease and those who are healthy.

“At that time, the research field was struggling with inconsistent results, largely due to the data on which they were based being insufficient. But when we got these findings at Christmas in 2007 and we saw that they were robust, I got so elated that I cried.”

The challenge when studying correlation with disease is often in taking the step from mapping genetic risk variants to understanding what function they have and what mechanisms in the body they affect. She hopes that the discoveries being made through GWAS, among others, will identify the specific mechanisms that affect energy balance and metabolism in humans.

“I want what we do to be translated into clinical benefit. That is why we also collaborate with various pharmaceutical companies, such as Novo Nordisk, Johnson & Johnson and Novartis.”  

 The possibilities of algorithms

She mentions the Covid-19 app, Covid Symptom Study, which is managed in Sweden by Maria Gomez and Paul Franks at Lund University, as an example of how AI and Big Data generate new possibilities for both decision-makers and individuals.

“It enables Covid-19 information to be gathered from users so as to assess risks and plan healthcare.”

Image analysis is another area in which Big Data has brought major improvements.

“Consider retina scans for example. I remember how highly qualified clinicians laboriously classified each retina image manually. What took several years to achieve in the past can now be done in a day by an algorithm.. That does not mean that machine learning tools should replace physicians, rather that it can be considered as a tool to facilitate clinical decisions”, she emphasises.

Ethical challenges

Big Data naturally presents challenges. One such challenge is the environmental impact of the large cooling facilities and the electrical power required for the computer halls, another is to retain cutting-edge talent within academia. Another important aspect is ethics.

“At BDI, we integrate ethics in all activities and have a large group working specifically on this. I also think it is important to consider diversity and minority representation. A large part of the data on which researchers base their work comes only from European populations, but if we want our research findings to be significant and beneficial to humanity as a whole, we need breadth. For example, it is completely crazy that some facial recognition algorithms can currently only process European faces.”

Loves a good confidence interval

Cecilia gets really inspired by robust associations and she observes that “everyone who knows me is aware that I love a good confidence interval”. 

“As researchers, we want to arrive at a correct conclusion and know how precise our results are. In this, Big Data shrinks the confidence interval. Because science is not subjective, it must be objective and based on facts. Research must be discussed and if someone is wrong, it needs to be pointed out and justified.”

She thinks that researchers and scholarly institutions must become better at demanding respect in public debate.

“Physicians or researchers have dedicated years of their lives to building their expertise. It worries me to see cultures and bubbles being fostered in which nobody trusts experts but instead googles their way to quick answers to complicated questions.”

The secret

Although Lindgren’s research work has been successful, it was not always obvious that she would remain in the profession. One secret has been to learn to enjoy the process and have that as a goal, rather than the end point.

“That has made me fearless and with little to lose. And I am also extremely curious. What I love about academic research is that it enables me to surround myself with like-minded curious people who ask difficult but important questions. What could be better?”

Text: Tove Smeds

Fun facts about Cecilia Lindgren

Doing: renovating her house, loving her family and friends
Reading: books in her book club. Currently, Where the Crawdads Sing by Delia Owens (so good!)
Watching: interior design and travel programmes
Wants: people to realise that kindness is something incredibly beautiful and generous
What you didn’t know about Cecilia: never go on a business trip with her – it always goes wrong and she has a library of business trip stories that sound completely incredible but are unfortunately true.

The Big Data Institute (BDI) is an interdisciplinary research institute that focuses on the analysis of large, complex, heterogeneous data sets for research into the causes and consequences, prevention and treatment of disease. BDI researchers develop, evaluate and deploy efficient methods for acquiring and analysing information for large clinical research studies. These approaches are invaluable in identifying the associations between lifestyle exposures, genetic variants, infections and health outcomes around the globe. The BDI is part of the Li Ka Shing Centre for Health Information and Discovery at the University of Oxford.
Source: The Big Data Institute (BDI)
April 26, 2021

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