{"id":1107,"date":"2022-06-27T02:35:08","date_gmt":"2022-06-27T02:35:08","guid":{"rendered":"https:\/\/joshmitteldorf.peachpuff-wolverine-566518.hostingersite.com\/?p=1107"},"modified":"2022-06-28T22:04:16","modified_gmt":"2022-06-28T22:04:16","slug":"lifespan-of-harold-katchers-rats","status":"publish","type":"post","link":"https:\/\/scienceblog.com\/joshmitteldorf\/2022\/06\/27\/lifespan-of-harold-katchers-rats\/","title":{"rendered":"Lifespan of Harold Katcher’s Rats"},"content":{"rendered":"

Preliminary results from lifespan studies with E5<\/strong><\/p>\n

Harold Katcher has developed a protocol for lab rats using intravenous injection with a blood plasma fraction he calls \u201cE5\u201d. Three years ago, he announced that treated rats evinced many features of rejuvenation, including improvements in grip strength, endurance, and learning capacity. Two years ago, he announced that treated rats also were epigenetically younger, according to a rodent methylation clock developed by Steve Horvath.<\/p>\n

This year, with a grant from Heales Foundation, Harold and his partner Akshay Sanghavi have supervised a trial in which older rats were treated with E5 and then allowed to live out their full lifespans so we might know whether epigenetic and phenotypic rejuvenation translate into increased life expectancy. Just this week, I obtained from them birth and death data for the experimental rats. There were 8 control rats, untreated, all dead, and 8 treated rats, 5 dead and 3 still living.<\/p>\n

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Executive summary of my findings:<\/strong>\u00a0At any given age, treated rats are 4x less likely to die; but translated into life expectancy, this is less impressive. The rats are living a little longer, but not nearly so much as their methylation age would have predicted. There is good evidence for compressed morbidity \u2014 treated rats are healthier later in life, and their deaths are less spread out in time than control rats. Caveats: All rats in the epigenetic experiment were male, while all rats in the lifespan study were female. Also, the protocol was initiated at a later age in the lifespan study compared to the epigenetic study.<\/p>\n

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Raw data:\u00a0<\/strong>Time is the rats\u2019 age in days. \u201cDeath\u201d =0 indicates that 3 of the rats are still living. Group 1 is control, Group 2 is rats treated with E5.<\/p>\n

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Time<\/td>\nDeath<\/td>\nGroup<\/td>\n<\/tr>\n
1034<\/td>\n1<\/td>\n1<\/td>\n<\/tr>\n
1064<\/td>\n1<\/td>\n1<\/td>\n<\/tr>\n
1069<\/td>\n1<\/td>\n1<\/td>\n<\/tr>\n
1155<\/td>\n1<\/td>\n1<\/td>\n<\/tr>\n
1158<\/td>\n1<\/td>\n1<\/td>\n<\/tr>\n
1159<\/td>\n1<\/td>\n1<\/td>\n<\/tr>\n
1161<\/td>\n1<\/td>\n2<\/td>\n<\/tr>\n
1173<\/td>\n1<\/td>\n2<\/td>\n<\/tr>\n
1179<\/td>\n0<\/td>\n2<\/td>\n<\/tr>\n
1183<\/td>\n1<\/td>\n2<\/td>\n<\/tr>\n
1193<\/td>\n1<\/td>\n2<\/td>\n<\/tr>\n
1197<\/td>\n1<\/td>\n1<\/td>\n<\/tr>\n
1200<\/td>\n1<\/td>\n1<\/td>\n<\/tr>\n
1209<\/td>\n0<\/td>\n2<\/td>\n<\/tr>\n
1209<\/td>\n0<\/td>\n2<\/td>\n<\/tr>\n
1218<\/td>\n1<\/td>\n2<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n

How this data is analyzed<\/strong><\/h2>\n

It is conventional and, IMO, also reasonable that the data on age at death are interpreted as a \u201cprobability of mortality\u201d. Of course, deaths spread over a greater time period indicates a lower rate of mortality. Less intuitive, the rate of mortality is based on the number of rats that remain alive at any given time, and not on the total number of rats. Thus, when the first rat dies, its probability of mortality is just \u215b, but when the last rat dies, its probability of mortality is 1.0.<\/p>\n

If a rat is still living it may contribute to the denominator only for rats who died earlier, and not for rats who died later.<\/p>\n

Using these conventions, I produced the following plot for probability of mortality for the two groups. I have plotted probability of mortality on a log scale because it is an empirical fact that probability of death increases exponentially with age. This is called the \u201cGompertz rule\u201d. If the Gompertz rule holds, then we expect the plot on a log scale to be a straight line. I have drawn the best straight line through the two sets of points.<\/p>\n

\"\"<\/p>\n

The Gompertz distribution is characterized by two numbers. One is the base mortality rate, which is related to how early the animals start dying. The other is the mortality rate doubling time. The probability of death doubles again and again over the life of the animals. A short doubling time indicates that the deaths are all bunched together, and a long doubling time indicates that the deaths are spread out over a broader range of ages.<\/p>\n

You can see that, compared to controls, the treated rats started dying later and that their mortality doubling time is shorter, with deaths bunched more closely in age.<\/p>\n

There is substantial uncertainty in these conclusions because of the small number of rats, but there is enough data here to give us confidence in the basic conclusions:<\/p>\n